Quantum Fog’s weight in bnlearn units

In a recent blog post entitled “R are Us. We are all R now”, I expressed my great admiration for the R statistical computer language, and I announced the addition to the Quantum Fog (QFog) GitHub repository of a Jupyter notebook called “Rmagic for dummies” which explains how something called Rmagic allows one to run both Python and R in the same Jupyter notebook.

In 2 other earlier blog posts, I also expressed great admiration for something else, bnlearn, an open source computer program written in R by Marco Scutari for learning classical Bayesian networks (cbnets) from data. I consider bnlearn the gold standard of bnet learning software.

The main purpose of this blog post is to announce that the QFog GitHub repo now has a folder of Jupyter notebooks comparing QFog to bnlearn. This is a perfect application of Rmagic to comparing two applications that can do some of the same things but one app is written in R while the other is written in Python. Pitting QFog against bnlearn is highly beneficial to us developers of QFog because it shows us what needs to be improved and suggests new features that would be worthwhile to add.

QFog can do certain things that bnlearn can’t (most notably, QFog can do both classical and quantum bnets, whereas bnlearn can only do classical bnets), and vice versa (for instance, bnlearn can do bnets with continuous (Gaussian) node probability distributions, whereas QFog can only handle discrete PDs), but there is much overlap between the 2 software packages in the area of structure and parameter learning of classical bnets from data.

A cool feature of the folder of Jupyter notebooks comparing bnlearn and QFog is that most notebooks in that folder can be spawned and run from a single “master” notebook. This amazing ability of the “master” notebook to create and direct a zombie horde of other notebooks is achieved thanks to an open source Python module called “nbrun” (notebook run).

Quantum-Ready Software

Quantum Fog is “quantum-ready” software: it has a parameter “is_quantum” in many of its functions which allows you to switch between Classical Bayesian Networks (is_quantum=False) and Quantum Bayesian Networks (is_quantum=True)

(footnote) I am not the first to use the term “quantum-ready”. I first heard it used by Henning Dekant. A Google search conducted before writing this blog post led me to discover that the company 1Qbit has also used this term in the past in its promotional literature

R are us. We are all R now.

I have long been an enthusiastic proponent of R, a computer language designed for doing statistical analysis. In fact, 7 years ago I wrote a post in this blog entitled “Addicted to R”.

Our company (artiste-qb.net) has been publishing software written mostly in Python. The Python ecosystem includes a very nice statistical package called Pandas, whose authors profess much love for R and unabashedly admit that they were trying to copy the best of R’s statistical functionality and bring it to Python users. This is fine and good, but is not enough, is it?

R has been around for a long time (since 1993 according to Wikipedia), and during that time it has managed to accumulate a formidable number of highly useful extension packages and a very large and passionately committed community of fans. As good as Pandas is, it would be a pity and outright foolish if our company and others in the same boat ignored R’s rich libraries and numerous users.

So I was elated when Tao Yin, a member of our company, introduced our company members to rpy2 and its extension Rmagic. Rmagic allows one to invoke R functions inside a Jupyter notebook running with a Python kernel. So in a single Jupyter notebook, you can call both Python functions and R functions in the same cell, or have some cells running just R and others running just Python. And of course, variables can be exchanged easily between R and Python within that notebook. So we are all R now. And Python too.

I’ve only known about Rmagic for about a week so I’m a newbie at it. Fortunately, even though rpy2/Rmagic is very sophisticated software under the hood, it’s API (Application Programming Interface) is quite simple and intuitive. I wrote a Jupyter notebook called “Rmagic for dummies” that I hope will convince you that Rmagic is very powerful yet easy to use.

The Bizarre History of Cambridge Quantum Computing (CQC Ltd)

Cambridge Quantum Computing (CQC) is a very British startup in the field of quantum computer software with a short but bizarre history that I find humorous. A case of fact being funnier than fiction.

CQC was founded in 2015 by Ilyas Khan. According to the Wikipedia article on Ilyas, which was probably written by himself, he comes to the QC business with no scientific degrees or programming experience of any kind. His training and experience are mostly in investment banking and philosophy. Here are some excerpts from the Wikipedia article:

“Khan is a merchant banker by training and started his career at the London firm of J. Henry Schroder Wagg & Co. Ltd. He was also the owner of the famous English football team Accrington Stanley and is its Patron [2] and the founder and publisher of the Asia Literary Review.[3]”

“His special interests include philanthropy and Wittgenstein, and he is a member of the British Wittgenstein Society.”

“Khan has lectured and published papers on Ludwig Wittgenstein, among other subjects.”

“In 2015 Khan founded Cambridge Quantum Computing,[5] which was selected by Bloomberg L.P., as a business Innovator 2016,[6] he has also published on the subject of Quantum Information Processing [7]”

Apart from having a warm & fuzzy feeling for quantum subjects, it’s not clear that Khan understands the underpinnings of QC enough to lecture about it or lead a QC software company prudently.

I first learned about CQC when the press went crazy over the news that a Chilean investment group called Grupo Arcano led by Alberto Chang Rajii was going to invest $50 million in CQC. For instance, here is an article by Bloomberg announcing this:

Early Google Investor to Help Bring Quantum Computing to Markets (by John Detrixche, Aug 26, 2015, Bloomberg news)

The importance of Alberto Chang to CQC was quickly confirmed by his ascension to the top spot in the “Team” webpage of the CQC website. Here is that page on Mar 4, 2016, retrieved using the WayBack machine. Click to enlarge.

All mention of Alberto Chang has disappeared from the latest reincarnations of the CQC “Team” webpage. What happened?

Well, if you google “Alberto Chang Rajii” “pyramid scheme”, you will find lots of news articles in English about Chang. (Or if you know Spanish, google the key words: Alberto Chang Rajii estafa)

For most of his career as a VC fund manager, Chang had been claiming that he had a business degree from Stanford, and that while at Stanford, he had met Sergey Brin and Larry Page, and had been one of the first investors in Google, an investment that had earned him millions. But Stanford and the founders of Google have now denied these assertions and Chang has been forced to recant publicly.

Grupo Arcano is (or was) based in Chile, with offices in Santiago-Chile, Miami-USA, London-UK and Sydney-Australia. Chang fled Chile to Malta on April 2016. He is a fugitive of the Chilean Law, which accuses him of running a pyramid scheme. His mother, a cofounder of Grupo Arcano, also tried to flee Chile but was snagged at the airport and is now under house arrest in Chile. Chang was seeking asylum in Malta but the Maltese government ultimately denied it and he awaits extradition to Chile. Chang’s assets have been frozen in the US and Europe, and the U.S. Securities and Exchange Commission has recently announced fraud charges against him.

Meanwhile, CQC continues chugging along. I just saw on Twitter that Khan is scheduled to give the keynote speech at some posh UK tech conference.