This website tells you how to understand key produce
value for quantum computing thanks to
mathematical computation
There is no need to beat around the bush: you will find plenty of “quantum computing experts”, explaining how quantum computing will be a revolution for your company and provide a “quantum software” to perform computations “exponentially faster” for any problem.
But have you ever realised that, despite your time and efforts, the more you get into quantum computing, the less you know where to go ?
This is normal.
The reason is that a majority of current promises, that mainly benefit of the quantum hype, are superficial.
For example :
- “Quantum computing will find new drugs to pandemic”
- “Quantum computing will break RSA encryption”
- “Exponentially faster solutions for optimisation and the travelling salesman problem”
All these sentences sound exciting – and sometimes they happen to be true with a long time scale ! – but one cannot turn a blind eye on quantum computing :
You will not solve your problem and generate scientific and (high) financial value with quantum computing if you rush for short term tricks only based on marketing or technology.
As would say Uncle Albert: “if quantum computing was so easy everyone would use it”.
He is right.
If you want to achieve a rare objective (understand quantum computing and use it for practical purposes), you will have to develop precious and rare skills.
This is where DEEP SKILLS come in the place.
For example :
- Keep a realistic vision for quantum based on mathematical computation
- Understand quantum error analysis and associated quantum “key performance indicators”
- Be able to assess the credibility of the latest LinkedIn post on a new solution for quantum hardware or software
- Structure your knowledge depending on your needs
- Identify good (and bad) use cases for quantum computing
These abilities are rare – and that is a good thing.
This means that your competitors do not make the effort to do develop them and external solutions will highly benefit from this lack of in-house skills.
Even better : these skills do not change over time.
Unlikely to « quantum hacks » and (that will be obsolete in 6 months), quantum knowledge centred on mathematical computation does not change on a daily basis.
This is excellent news – because if you focus your strategy on quantum computing, it is extremely hazardous to build on « small tactics » and ruinous if you only pay for solutions or hardware access without your own computational guard-rail…
Thus, as many companies that build quantum computing on sand and increase the quantum bubble, your strategy could collapse from day to day !
On the contrary, if your quantum strategy is based on a clear and realistic vision – you can be sure that mathematical foundations will not change on a daily basis.
This is why I am obsessed with these deep mathematical skills:
1 They are rare – so they give you an advantage for the quantum race
2 They do not change – then you know that you will always have a scientific guideline, whatever the technological updates
My story
I started research on mathematical computation in 2012 and never stopped since then.
This means that I spent all my professional career obsessed with one topic : How to understand deep mathematical mechanisms of scientific computing for industry.
And this is why this website is called “Heart of quantum”.
To me, research never was “just a way to make career in industry or academia”.
There is nothing wrong with this, of course, but mathematical research has been since the beginning a deeper passion.
You will find how I started in this video (a faire plus tard ?)
What matters to me is that you understand that I have been developing my vision on mathematical computation long before quantum computing and starting Heart of quantum.
My first project was a joint work with the Scientific Direction of Total energies and CERFACS. It was focused on the limits of High Performance Computing (HPC) and the “exascale” generation (1 000 000 000 000 000 000 operations per second, a billion of billion !) for numerical simulation. Scaling was a main issue as it was impossible to do as for the previous generations, simply the same things bigger.
I was learning from Françoise Chatelin, one of the faces of the golden era of numerical analysis, that contributed to define rules for finite precision computations on classical computers.
If you want to know more on this you can check here: todo
After some years of intense work, confirming the intuition that started my work with the Qualitative Computing group, it was clear that the intrinsic limitation of HPC was at the scientific level and not merely with technology. Forget about Moore’s law that is a marketing guideline for chip manufacturers. The real hindrance to parallelism is called nonlinearity and this is an issue that cannot be tackled at the algorithmic level or with processors improvement. This is a fondamental modelling problem that explains the differences between the relations between complexity, scaling and modelling. This is such an key question that it is developed here:
image lien à faire
At the same time, I realised that the algebraic structures I was working on were at the root of the quantum gates and operations for quantum simulation. In 2018, IBM came to present quantum computing at CERFACS. This is how I began my quantum journey. I proposed a new project with the same industrial partners and I soon realised that quantum computing may suffer from the same difficulties encountered in HPC.
There is a risk in shading scientific key problems behind necessary but still secondary matters. Thus I decided to share this experience and help people interested in quantum. This is how the Heart of quantum project started.
Remember one thing, both for classical and quantum computers:
there is no advantage in computing faster wrong results !