Lab rules

July 3, 2018

I left academic research one and a half year ago and I had time to think about this time spent there (10 years!), the good and the bad, the differences with the industry,… There would be a lot of things to say, but from a limited viewpoint, my own one. An in-depth social survey of the field would actually be necessary to understand the different mechanisms at stake in modern research. An almost impossible task given the size of the field and its various forms. Each area of science is a country, with its own language, its own culture and its own politics. I just want to write down some notes, a kind of elementary rules to survive and thrive in the world of modern research. I do not like some of these rules because they implicetely give credit to some aspects of modern science that I do not like. But before being able to change the parts we do not appreciate in the job, we have to be accepted in it by your fellow researchers. This is the purpose of these rules.

  • rule number 1: become a paper producing machine. Research is a machine oriented towards the production of articles.  Everything from grants to promotions to collaborations is calibrated on the papers you produce. This is not necessarily easy to accept. You may think that you have to write a paper once you have well rounded results with a consistent theory and the associated experimental data. This was probably the case decades ago. This is not the case now. You have to set objectives of production: one or two journal articles a year, one conference proceedings, review papers, posters, talks, meeting presentations to complete your stock. And you have to build your research plan around these objectives: which data are required, who will your coauthors be, which aspect of your research topic you will deal with it. From there, you establish your cooperations, your experimental plan, your simulation time… Papers are the blood of your work, without it, you cannot exist.
  • rule 2: networking. Modern science is not a solitary work. Even if you think that you can do it only alone because of concentration, consistency, whatever excuse not to talk with others. The myth of the solitary genius is wrong. Yes, all popular articles focus on individuals, nobel prizes and most other science prizes are awarded to individuals. But this is just for the image of science, to consolidate the myth of the genius in the society. Modern science is made by collaboration. First, because you need other viewpoints, even when you think you have the solution. Science is a community activity. It is its essence, its core feature. More practically, you will get grants only when you are able to build collaboration, you will get prestige when you will be able to leverage a network, you will get students, hardware, computation time one you will be at the head of a team, interdisciplinary, international and inter-cultural. So chat with your fellow, propose ideas that can attract them to your work. And keep contact. You will see that conferences are far more useful when people known that you are the entry point for a big network of scientists. Your field of research is like a big party: the more fresh blood you have, the more fresh blood will come and the bigger the party.
  • rule 3: lobbying your ideas. You have a revolutionary idea, you have the corresponding theory, the associated data, a well-rounded, clear, scientifically accurate paper, you publish it and nobody pays attention. This is normal. An idea, even with convincing arguments, takes years to be accepted. People have a limited attention span for your topic because of the multitude of their own projects. They do not have time to go deeply in a paper to understand a new idea. They first have to get used to it. So you have to exercise an intense lobbying: explain, explain and explain again. Never lose patience. It is even more difficult when it is about a controversial issue or project or whatever crazy experiment you want to propose. Never hesitate to propose it. Everybody will say no way. Do not stop, come again and again and you will see resistance fade away. This is purely human psychology. Scientists are not pure rational machines. You have to overcome many psychological obstacles in the fead of your fellow scientists and all it requires is time.
  • rule 4: proper communication. You have the formal scientific communication, which is the foundation of research. This is where the knowledge resides in and it has to follow very strict rules in term of structure, clarity, logics, accuracy. Never ever try to lower these standards. But you have other channel of communications, more informal: talks, seminars, coffee-machine small talks. This is where you have to develop the story of your research. Make it exciting, entertaining; it is the gate to your world, to your research; this is where your colleagues want to enter to participate to the big party that you organize in your small area of science. Like all stories, it requires a proper narrative structure, its moments of tensions, its cliffhangers. Work on it, it is a funny, human activity.

Thinking of other rules?


Look to windward

September 27, 2016

I have always been fascinated by the title of this novel by Iain M. Banks, even though I have never really understood the true meaning of it in the story. Whatever, I have this expression in mind now that I am trying to build a team for a project of mine.

And the wind you feel when you are selling your project to potential teammates is not a light breeze grazing the hair, it is a violent hurricane breaking each part your body. Looking to windward is painful.

The project is, in my opinion, not bad: there is a good idea, a potential market and possible long-term developments. And I kept its objectives reasonable and achievable with a modest amount of funding to start with. The technical challenge of developing the software is limited as well.  Thus, it is a nice medium-sized project with a vision, a well-formed pitch, technical feasibility and potential to reach a market.

Yet, what hell it is to find people ready to participate to it. I did not ask for 100%, no, it is not necessary. It can be a side-project at the beginning. But, I get during the discussions all the risks and possible imaginable failures, I am explained the hard competition, the difficulty to get funded, the bugs, the security leaks and other trouble a code can offer. I do not even imagine the reaction if I would propose to start a new SpaceX 🙂

It is incredible how people can be pessimistic. Is it because they care of you and want to prevent you from suffering? Is it animal instinct to escape the danger? I do not know, maybe a mix of these. No wonder that successful entrepreneurs deploy a reality distortion field: it is the only way to deal with the surrounding negativity.

The positive aspect is that you learn to polish the presentation of your project and to improve the counter-arguments. The negative aspect is that I still have not found a soul to share this project with.

The Wind rises for the engineers

July 15, 2014

The latest (and probably last) creation of Miyazaki is about the (fictionalized) life of the plane designer Jiro Horikoshi, the creator of the Mitsubishi A6M Zero, which gave nightmare to many US pilots during WWII. It was a huge success in Japan.

I will be honest from the beginning: this is not my favourite Miyazaki: the magics does not work and I do not know exactly why: perhaps the character of the hero is not enough worked out, a bit too dull. Or the tragic love story, the purpose of which is not clear; he wanted perhaps to show that engineers have an heart in addition to a brain.

Yet, it is Miyazaki and the film is still a masterpiece. I have three main elements that attracted my attention and where I thought “yes, this is like that!”.

  • first, the dreams as a child: which aerospace engineer did not have dreams of sky or space when he was a child? Which enginerr did not imagine the perfect machine in his daydreams. You dream, you study, you take the low level jobs in an aerospace company and you climb the ladder. 
  • Second, the relation with the hardware. There are two beautiul scenes (for an engineer): On his first day at Mitsubishi when he asks whether he can see the assembly of the plane in the workshop; the foreman is happy to see that at least one guy from the design office is interested in the hardware. And the second scene where the design team receives a sample of the new ultra-light aluminium alloy (I wonder if it is the 7075 developed Sumitomo Metal). and they are all bewildered by this apparently mundane rod of metal.
  • And to finish, the complex relations between the dreams of an engineer and the hard reality of a war. It is of course controversial: we do not know exactly what really happened in the mind of Horikoshi. He is depicted in the film as rather little concerned by the  military aspect of his job.


All in all, I would recommend the film if you are engineer, especially to watch the lost art of the slide-rule.  

Reliability of high level scientific softwares

July 14, 2014

Yes, Mathematica and your new release with more than 700 new functions, I am hinting at you. I am wondering how programs so advance as you can be reliable.
Other softwares are in the same case, but S. Wolfram is rather explicit in his blog about making Mathematica the second, more advanced brain, of every scientist (for a small transfer of money).

The question that I have when I use this kind of software is the following:

How am I a sure that the software gives the right answer to my question?


This question has two parts:

  • first, how does Wolfram insures that the program has no bug? It is a closed proprietary system. Of course, you have a feedback system, but still, you need the bug to be obvious to detect it. When you do science, you are in quicksands: you are sure of nothing and you need some stable ground to progress.
  • second, these codes offer more and more advanced functions: how can I be sure that I use the function in the proper way. The problem is that for a same function, the code can branch on different algorithms depending on the range of your parameters and it is not always obvious to understand the limitations of each algorithm. Of course, you can call the hotline, you can follow trainings but it costs money, added to the initital cost of the license.

In my opinion, this kind of general purpose software should be kept for basic general computing; a kind of enhanced pocket calculator. As soon as you need to do more complex things, you need anyway to understand what happens under the hoot; so you have to use an open code, so that you can check if everything goes right during the simulation.


June 25, 2014

There are more and more talks of open or citizen science. For the moment, the main focus is on the publishing system and the way to remove it from the hands of a bit too greedy professional publishers. Two other aspects are the experimentation and numerical science, two money eaters of first class. There is a lot of to say about publishing and numerical science, but I want to focus today on the experimental part and how the maker movement is about to “make” things change in science, provided that we address the right type of issue.

We don’t need to be a fortune-teller to foresee that giant experiments like LHC or ITER or NIF will absorb more and more of the public funding for science. They require money, manpower and a lot of paperwork, changing the way scientists are dealing with experiments. I have to be clear: these experiments are useful and enable to develop a lot of spin-off technologies. The problem is that small or medium-sized experiments are cancelled because of the resulting lack of funding. And believe me, there are a lot of things to learn from room-sized or table-sized testbed. Actually, it is even the only way to keep the contact with reality.

If most institutes or labs start to give up the work on this type of old-fashioned experiments, it can be an opportunity for citizen science. The idea would be to have hackerlabs dedicated to one or several experiments, with access for everybody, just like a hackerspace. You go there to learn how to build a testbed, to carry out experiment, to imagine new experiments. All this with the support of a team of professional experimenters and access to a full-fledged workshop.

What do you gain with respect to a classical lab?  First, independence and flexibility: you choose your hackerlab, your experiment, your objectives, your agenda. Second, you keep hands on real stuff: you learn why experimenting is hard: why it is not enough to push a button to get ready-to-use nobel prize-graded results. Third, you can use as template the structure of the maker world, inclusive the communication system, to present your experiments, your results. You can even imagine a remote control of your testbed, creating your plasma discharge from your bed (I used to trigger my digitizers from the seashore, the best place to think).

And you would not have to justify in advance the choice of every technology you use (“because it’s fun” has always been a bad justification in the academic world). Finally, a good place to use Google Glasses integrated to your experimental process!

Efficient Mega-Engineering (part 2): birth of a project

August 8, 2011

A project can be seen as a compound of two ingredients: physics and engineering. It is a distinction that I dislike but which is all the same useful to understand how big project starts. In nuclear fusion, the physics tells which plasma configurations are the best to keep the particles confined and reach the ignition and engineering tells what kind of magnetic coils and of infrastructure is necessary to achieve this configuration. There is actually a balance to find between physics and engineering: the less  you understand the physics, the more you have to use heavy engineering to palliate this lack of knowledge.


We can take the example of toroidal magnetic confinement configurations for fusion research: one possible solution is the spheromak, where the plasma self-generates its own magnetic field, a kind of dynamo effect. It requires almost no external structure to keep confined; the problem is that it is in a permanent turbulent state which is hard to understand and to control; as a result, its confinement time is quite low (and the reduced amount of time and money accorded to this kind of projected prevented any significant progress on this type of facility). The solution chosen was to reduce the freedom of plasma by containing it inside a magnetic field. A lot of more engineering is involved and to limit its complexity, an axi-symmetric configuration was favoured; it was the birth of the tokamak. The problem is that this configuration is stable only if you induce a toroidal current inside the plasma, which has a deep impact on its physics (creation of instabilities). Therefore, another idea was to go a step further in engineering complexity with the stellarator and to give up the idea of axi-symmetry by twisting the magnetic field so that no more plasma current is necessary for the confinement. This short overview of the different types of fusion facilities show the difficulty to find the right balance between engineering and physics.


Aerospace is also a significant example: what prevents us from reaching Mars or even the other stars? The fact that it is impossible to find a balance between physics and engineering. Either you want to use a well-known physics based on chemical or electrical propulsion and, in this case, the cost of engineering necessary to solve the obvious shortcomings of these methods is too huge to be realistic. Or you want to use advanced physics (antimatter, warp drive or whatever exotic engines) and you areconfronted with the lack of knowledge.

Consequently, a project can start when the physics is sufficiently understood to be implemented in an engineering infrastructure with a limited level of complexity, i.e. which is tractable in terms of cost and of management (of interfaces).


Different scenarios can happen and trigger the start of a project: an unexpected discovery (for instance the H-mode confinement in tokamaks in 1982), the improvement of the technology (advances in superconductors), improvement of engineering tools (CAD, collaborative frameworks) and so on. In most cases, we have iterations over long times where both physics and engineering indicate the direction to follow in their respective fields of research.

One major difficulty in mega-projects is that the physics is multifaceted, involving many areas of interest with different conceptual tools; people in charge of preliminary designs need to have a large general culture both in physics and engineering and adequate tools to survey experiments and theoretical works with a possible impact on their projects.

The pre-design of a project is the first milestone in the connection of physics and engineering. We will see in a next post that it is the point where most of the difficulties met by a project in the later steps are rooted in.

Efficient Mega-Engineering (part 1)

July 22, 2011

Well, you probably know it, the space shuttle’s era is now over. Like many other space enthusiasts, I wonder what the future will be about: commercial space access, tourism are certainly part of this future, with, more particularly, the prodigious development of SpaceX and its launcher Falcon. But this is not what interests me in space, I like the exploration part, the discovery of new horizons, the possibility to travel even further away from mother planet. Consequently, I like projects like Icarus which thinks about the design of  an interstellar probe. With the present knowledge, it sounds unrealistic, at the limit of science fiction, but it is where the dream is, the excitation, the motivation.

This kind of project is what I call Mega Engineering: a project at the limit or even beyond technological or physics knowledge, with highly multidisciplinary interactions, all packed in a complex system, where several countries have to participate with intricate political issues. What is the difference with Big Engineering like the development of skyrockets, space shuttle, space telescopes, particle accelerators? These examples are mainly based on proven technologies and physics, the complexity comes from putting all these technologies together, the difficulty is there the system. Mega Engineering complexity comes both from the system and the technology and the physics. I think that nuclear fusion reactors can be put in this category, interstellar probes as well and even economical earth-to-orbit transportation. All these projects are based on a physics which is difficult to grasp, on a technology which is not mature and on an elaborate architecture.

I would like to have a look at the different stages of the development of a mega-engineering project, the difficulties associated to them,  and to explore the potential solutions to overcome these difficulties. Actually, for each problem, I will present two types of solution: one soft (by applying and improving existing methods) and one hard (nearing methods from science fiction).

Please, stay tuned for the first part, how the idea of a mega-engineering project comes to the light.

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