How to use the chemlambda collection of simulations

The chemlambda_casting folder (1GB) of simulations is now available on Figshare [1].

How to use the chemlambda collection of simulations? Here’s an example. The synthesis from a tape video [2] is reproduced here with a cheap animated gif. The movie records the simulation file 3_tape_long_5346.html which is available for download at [1].

That simple.

If you want to run it in your computer then all you have to do is to download 3_tape_long_5346.html from [1], download from the same place d3.min.js and jquery.min.js (which are there for your convenience). Put the js libs in the same folder as the html file. Open the html file with a browser, strongly recommend Safari or Chrome (not Firefox which blocks with these d3.js animations, for reasons related to d3). In case your computer has problems with the simulation (I used a macbook pro with safari) then slow it like this: edit the html file (with any editor) and look for the line starting with

return 3000 + (4*(step+(Math.random()*

and replace the “4” by “150”, it should be enough.

Here is a longer explanation. The best would be to read carefully the README [4].
“Advanced”: If you want to make another simulation for the same molecule then follow the steps.

1. The molecule used is 3_tape_long_5346.mol which is available at the library of chemlambda molecules [3].

2. So download the content of the gh-pages branch of the chemlambda repository at github [4] as explained in that link.

3. then follow the steps explained there and you’ll get a shiny new 3_tape_long_5346.html which of course may be different in details than the initial one (it depends on the script used, if you use the random rewrites scripts then of course the order of rewrites may be different).

[1] The Chemlambda collection of simulations

[2] Synthesis from a tape

[3] The library of chemlambda molecules

[4] Chemlambda repository (readme)

The chemlambda collection is a social hack, here’s why


People from data deprived places turn to available sources for scientific information. They have the impression that Social Media may be useful for this. Reality is that it is not, by design.

But we can socially hack the Social Media for the benefit of Open Science.

Social Media is not fit for Open Science by design. They are Big Data gatherers, therefore they are interested not in the content per se, but in the metadata. The huge quantity of metadata they suck from the users tells them about the instantaneous interests and social links or preferences. That is why cat pics are everywhere: the awww moment is data poor but metadata rich.

Open Science has as aim to share scientific data and rigorous validation means. For free! Therefore Open Science is data rich. It is also, by design, metadata poor, because at least if a piece of research is not yet popular, there is not much interaction (useful for example to advertisers or to tech companies or govenrnments) to be encoded in

The public impression is that science is hard and many times boring. There are however many people interested in science, like for example smart kids or creative people living in data deprived places. There are so many people with access to the Social Media so that, in principle, even the most seemingly boring science project may gather the attentions of tens of thousands of them. If well done!

Such science projects may never see the light of the media attention because classical media works with big numbers and very low level content. Classical media has still to adapt to the new realities of the Net. One of them is that the Net people are in such a great number that there is no need to adapt a message for a majority of people which is not, generically, interested in science.

Likewise, Social Media is by design driven by big numbers (of metadata, this time). They couldn’t care less about the content provided that it generates big data exhaust (Zuboff, Big other: surveillance capitalism and the prospects of an information civilization).

They can be tricked!

This was the purpose of the chemlambda collection: beautiful animations, data rich content hidden behind for those interested. My previous attempts to use classical channels for Open Science gave only very limited results. Indeed, the same is true for a smart kid or a creative person from Africa.

If you are not born in the right place, studied at the right university and made the right friends then your ideas will not spread through the classical channels, unless your
ideas are useful to a privileged team. You, smart kid or creative person from Africa, will never advance your ideas to the world unless they are useful first not to you, but to privileged people from far away places. If this happens, the best you can expect is to be an useful servant for them.

So, with these ideas and experiences, I tried to socially hack the Big Data gatherers. I presented short animations (under 10s) obtained from real scientific simulations. I chose them among those which are visually appealing. Each of them can be reproduced and researched by anybody interested via a GitHub repository.

It worked. The Algorithmic Gods from Google decided to make chemlambda a featured collection. I had more than 50 000 followers and more than 50 millions views of these scientific, original simulations.

To compare, another collection, dedicated to censorship on social media, had no views!

I shall make, acording to my access to data, which is limited, an analysis of people who saw the collection.

It seems to me that there were far more women that men. Probably the algorithms used the prior that women, stupid as they are, are more interested in pictures than text. Great, let’s hack this stupid prior and turn it into a chance to help Women access to science 🙂

There were far more people from Asia and Africa than from the West. Because, of course, they are stupid and don’t speak the language (English), but they can look at the pictures. Great, let’s turn this snobbery into an advantage, because they are the main public which could benefit from Open Science.
The amazing (for me) popularity of this experiment showed that there is something more to dig in this direction!
Science can be made interesting and remain rigorous too.

Science and art are not as different as they look, in particular for this project the visual arts.

And the chemlambda project is very interesting, of course, because it a take on life at molecular level done by a mathematician. The biologists need this, not only mathematical tools, but also mathematical minds. Biologists, as the Social Media companies, sit on heaps of Big Data.

Finally, there is the following question I’d like to ask.
Scientific data is, in bits, a tiny proportion of the Big Data gathered everyday. Is tiny, ridiculously tiny.

Question: where to put it freely, so that it stays free and is treated properly, I mean as visible and easy to access as a cat pic? Would it be so hard to dedicate something like 1/10 000 of the servers used for Big Data in order to keep Open Science alive? In order to not let it rot along with older cat pics?

Preparing the microscope

For a new experiment.


If you want to discuss then here are some possibilities: which supposes that you make first a mail account at tutanota or open an issue at my chemlambda repository and propose me your way. Mind that if I don’t respond you then it means that either I did not got the message or I ignore your message because what you want can be deduced by using the already available public information.


Google segregation should take blame

Continuing from the last post, here is a concrete example of segregation performed by the corporate social media. The result of the US election is a consequence of this phenomenon.

Yesterday I posted on Google+ the article Donald Trump is moving to the White House, and liberals put him there | Thomas Frank | Opinion | The Guardian    and I received an anti-Trump comment (reproduced at the end of this post). I was OK with the comment and did nothing to suppress it.

Today, after receiving some more comments, this time bent towards Trump, I noticed that the first one disappeared. It was marked as spam by a Google algorithm.

I restored the comment classified as spam.

The problem is, you see, that Google and Facebook and Twitter, etc, all corporate media are playing a segregation game with us. They don’t let us form opinions based on facts which we can freely access. They filter our worldview.  They don’t provide us means for validation of their content. (They don’t have to, legally.)

The idiots from Google who wrote that piece of algorithm should be near the top list of people who decided the result of these US elections.


UPDATE: Bella Nash, the identity who posted that comment, now replies the following:

“It says the same thing on yours [i.e. that my posts are seen as spam in her worldview] and I couldn’t reply to it. I see comments all over that  google is deleting posts, some guy lost 28 new and old replies in an hour. How the hell can comments be spam? I’m active on other boards so I don’t care what google does, it’s their site and their ambiguous rules.”

Screen Shot 2016-11-11 at 10.47.16.png

Theory of spam relativity 🙂


To be clear, I’m rather pleased about the results, mainly because I’m pissed beyond limits by these tactics. This should not limit the right to be heard of other people, at least not in my worldview. Let me decide if this comment is spam or not:

“In Chicago roughly a thousand headed for the Trump International Hotel while chanting against racism and white nationalism. Within hours of the election result being announced the hashtag #NotMyPresident spread among half a million Twitter users.

UPDATE 2: Some people are so desperate that I’m censored even on 4.chan 🙂 I tried to share there this post, several times, I had a timeout. I tried to share this ironical Disclaimer


which should be useful on any corporate media site, and it disappeared.

The truth is that the algorithmic idiocy started with walled garden techniques. If you’re on one social media site, then it should be hard to follow a link to another place. After that, it became hard to know about people with different views. Discussions became almost impossible. This destroys the Internet.

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