Quantum Bayesian Networks

January 31, 2017

Qubiter and IBM-QASM2 can now communicate via sign language

Filed under: Uncategorized — rrtucci @ 5:15 pm

I’ve always liked mime (Marcel Marceau, Charlie Chaplin,…), physical comedy (using body motions as a source of humor, like Italians do) and the closely related sign-language for the deaf. Sign language can be extremely clever, inventive and expressive. For example, this is how to say Donald Trump in sign-language:

But enough about Trump, who threatens to suck the air and joy out of every conversation. The official purpose of this blog post is to advertise the fact that now Qubiter (https://github.com/artiste-qb-net/qubiter) can convert quantum circuits from its native language to that of IBM, so that you can generate quantum circuits using Qubiter and then run them on the IBM hardware (assuming that those circuits have only 5 qubits and less than about 80 gates)

Recently, the folks at IBM Quantum Experience (IBM-QE) have introduced some very nice enhancements to their QC cloud service. The graphical user interface (GUI) of their website has been revamped. They have also opened two new repositories on GitHub,

  1. IBMQuantum/QASM
  2. IBMResearch/python-sdk-quantum-experience

Repo 1 introduces their new “intermediate level language” QASM2.0 with a paper in Latex/pdf that teaches the in and outs of their language. This repo also includes samples of qasm2 scripts of two types: some that can be run on their current hardware, and some that can’t be but can still be simulated using their numerical simulator.

Repo 2 gives some Python code for accessing the IBM-QE service via a python script or Jupyter notebook.

To keep up with these IBM enhancements, Qubiter now includes a new file called Qubiter_to_IBMqasm.py This file contains a class of the same name that translates Qubiter “English files” to IBM QASM files. You can write a simple Python script that reads the qasm file produced by the class Qubiter_to_IBMqasm and inputs that string into the code of Repo 2. That way, you don’t even have to visit the IBM-QE website to run your q circuit on their hardware. Alternatively, you can manually copy&paste the qasm file produced by the new Qubiter class into the “QASM Editor” at the IBM-QE website.

The current IBM-QE hardware doesn’t allow all possible CNOTs among its 5 qubits. Out of the 5 qubits 0, 1, …, 4, only qubits 1, 2 and 4 can be physical targets of an elementary CNOT. Also, some pairs of qubits cannot be the two ends of an elementary CNOT because they are physically disconnected. The class Qubiter_to_IBMqasm overcomes both of these limitations. It allows CNOTs among any pair of qubits. Every elementary CNOT that is disallowed is replaced by a compound CNOT; i.e., either 1 or 4 elementary CNOTs (and a bunch of Hadamards) that is equivalent to the original CNOT and is allowed.

January 20, 2017

Microsoft Quantum Computing Olympics QIP2017 Comes to A Close Today

Filed under: Uncategorized — rrtucci @ 8:16 pm

Today was an ominous day for the Galaxy. QIP2017 came to a close and Donald Trump was inaugurated as president of the United States…

Today, attendees of QIP2017 got these two postcards with an attached note saying: “Microsoft bids you a fond farewell and would like you to have these 2 commemorative postcards as a final bit of swag to remember QIP2017”

January 15, 2017

A photograph of a dangerous thug

Filed under: Uncategorized — rrtucci @ 2:51 am

The purpose of this post is to remind my readers of Microsoft’s thuggish history, as described by the NYT. Will Microsoft be a repeat offender in the emerging field of quantum computing? IMHO, there are some ominous signs that it has started to move full-steam in that direction.

Check out this great article:

MICROSOFT’S WORLD: A special report.; How Software’s Giant Played Hardball Game,By Steve Lohr and John Markoff, New York Times, Oct 8, 1998

Next I will quote the beginning of the article. I recommend that you read the whole thing. The article doesn’t tell the half of it. For example, it doesn’t describe Microsoft’s vigorous attempts to destroy Linux OS and the open software movement. And any company that posed the smallest threat to its Office suite of apps.

In the summer of 1995, a whiff of revolution was in the air in Silicon Valley. The Internet offered a new deal in computing, a fresh opportunity for entrepreneurs to try to break the Microsoft Corporation’s firm grip on the personal computer software business. Leading the challenge was the Netscape Communications Corporation, whose software for browsing the World Wide Web had ignited the Internet boom.

James H. Clark, Netscape’s chairman, spoke boldly of attacking Microsoft head-on. He borrowed imagery from the movie ”Star Wars,” referring to Microsoft as the Death Star and Netscape as the leader of a rebel alliance.

Microsoft answered with a vengeance. It dispatched hundreds of programmers to work on a competing browser and poured many millions of dollars into marketing it. It prodded computer makers and others to distribute its browser, folded the browser into its industry-dominant Windows operating system and gave the browser away free — a campaign intended to ”cut off their air supply,” as a senior Microsoft executive described it.

But it’s not only competitors like Netscape that have encountered Microsoft’s force. Microsoft’s partners, its corporate customers and professional investors who finance new ventures have all collided with it.

A close look at Microsoft’s no-holds-barred push into the Internet software business offers a window into the ways the company uses its market muscle to influence the behavior of virtually every player in the industry.

Some of the cases recounted here figure prominently in the suit brought by the Justice Department and 20 states, scheduled to go to trial later this month, charging that Microsoft at times went too far — and violated antitrust laws.

Regardless of the legal outcome, previously unreported details about incidents in the suit and the other examples provide a more complete picture of Microsoft in action.

*When the Compaq Computer Corporation considered loading Netscape’s browser instead of Microsoft’s on its machines, Microsoft threatened to stop selling its Windows operating system to the big personal computer maker. Compaq, Microsoft’s largest customer in the industry, quickly changed its mind.

*After Spyglass Inc. began supplying Microsoft with its early browser technology, Microsoft announced that it would give away its browser free. The timing came as a rude surprise to its partner Spyglass. The company lost most of its revenues almost overnight, as the technology, which it had also been licensing to companies besides Microsoft, suddenly became available free.

January 11, 2017

QIP2017 is next week

Filed under: Uncategorized — rrtucci @ 3:15 am

As I mentioned in my previous post, the QIP2017 conference will be held on Jan 16-20, 2017 at Microsoft HQ, the geometrical center of the DeathStar.

One cannot help noticing that Google, despite it’s considerable commitment to gate model quantum computing, did not sponsor or participate in any committees of Microsoft’s QIP2017. Was this an intentional boycott?

The quantum annealer crowd (DWave, NASA, Lockheed-Martin) has stayed away from QIP2017 too, except for a tiny company called 1Qbit. I do not include Google in that crowd because Google, despite what it seemed to claim when it first hired Martinis, seems to have abandoned quantum annealers to pursue gate model QCs almost exclusively.

All talks at QIP are summaries of papers that have been posted at arXiv months ago, so this conference is an academic version of a pre-scripted American political convention and an ad for MS. If you are not already aware of this, many if not most academic researchers are politicians (some very eager to be bought) first and researchers second. Since the papers have been available to anyone for months, any researcher needing to ask questions to the authors could have done so long ago at almost no cost via email or video conferencing. So it’s hard to justify the cost incurred by the researchers to attend such conventions (entrance fee ~ $400 + airplane fare + hotel costs, all courtesy of the taxpayer for NSF funded researchers)

Here are some materials that MS is circulating to promote the event. MS intends to use the occasion to show to the world the superiority of the MS race in quantum computing.

January 6, 2017

Pythonic Qubiter now has a quantum compiler. The Death Star doesn’t have one yet.

Filed under: Uncategorized — rrtucci @ 12:33 am

quantumsoftwaretwotypesAs I’ve mentioned many times before in this blog, Henning Dekant (in Toronto) and I (in Boston) founded about a year ago a quantum computer software company called Artiste-qb.netartiste-logo. Our two main products so far are the open source Python programs Quantum Fog and Qubiter. Both programs were originally written in C++, but now they have been rewritten in Python and improved in many ways. This blog post is to announce that the Pythonic version of Qubiter now has a quantum compiler. Hurray for the Rebel Alliance!

Quantum compilers have long been an interest of mine. As far as I know, I was the first one to use the term “quantum compiler” in a paper in the field of quantum computing. I did so in the following 1999 paper


By a quantum compiler I mean a software program that takes an ARBITRARY unitary matrix as input and decomposes it into a sequence of qubit rotations and CNOTs. In my opinion, quantum compilers that fit this description are useful, even necessary, if one wants to use quantum computers to do artificial intelligence. Because, whereas for most physics applications one can assume unitaries of the form U = e^{-itH} where H, the Hamiltonian, has a very special structure, in AI, the unitaries can have an ARBITRARY structure (not known a priori) that doesn’t come from a Hamiltonian with an a priori known structure.

That 1999 paper was the first one to propose using the CS decomposition of Linear Algebra to do quantum compiling. The C++ program Qubiter, which was first released open source simultaneously with the 1999 paper, was the first computer program that used the CS decomposition to do quantum compiling.

Since that 1999 paper, many papers have been written using the same CS decomposition algorithm as my paper, but not citing my work, because, truth be told, dishonesty is rampant among academic researchers.

Other papers have copied the term “quantum compiling” to refer to a task that is related but much less general than what I call quantum compiling, namely, the task of decomposing a single qubit rotation into a sequence of operations from a finite set of gates. The latter task is necessary for fault tolerant quantum computing and was first tackled by Solovay and Kitaev, but they did not refer to it as “quantum compiling”. Nobody did prior to my 1999 paper.

This blog, which is now 8-9 years old, has featured several posts about quantum compilers. These are my favorites:

And now, the latest gossip about quantum compilers.

Up to now, Microsoft’s main and only quantum computer program was Liqui|>, a heavily patented, closed source computer program written in an unpopular language called F#. For many years now, the main writers of Liqui|>, Dave Wecker and Krysta Svore, have been promising to be THE FIRST to provide a quantum compiler, and of course, never mentioning my work. In some papers, KS uses the term quantum compiler to mean the same thing as me, in other papers she uses it to mean software that does the Solovay-Kitaev decomposition. But I can state unequivocally that Liqui|> has no CS decomposition quantum compiler at the present time. So Qubiter is way ahead of them there.

But the plot thickens. Matthias Troyer is a professor at ETH Zurich that works part time, for big bucks, for Microsoft. He has written papers about Liqui|> with Dave Wecker and Krysta Snore. Hence many people were extremely surprised that on Dec. 23, 2016, Matthias and two of his students at ETH Zurich, Minion A and Minion B, released a computer program called ProjectQ that duplicates most of what Liqui|> does and is therefore in direct competition with it. However, ProjectQ is open source, written in Python, and under the Apache License. The suspense is unbearable. Does this mean that Liqui|> will be laid to rest, R.I.P., meaning Dave Wecker’s and Krysta Svore’s work for the last 5 years will be completely ditched? Stay tuned. Microsoft will be holding QIP 2017 on Jan 14-20. That QIP is going to be Microsoft’s 1936 Nazi Olympics, where they intended to dazzle the world with their superiority in quantum computing. Maybe then we will find out, by watching carefully the placement of the people on the main dais during the weapons parade, who is up and who is down.

Henning and I welcome all open source code, even if it is in competition with Qubiter.

IMHO, Qubiter is currently much better than ProjectQ. For one thing, they claim they have a quantum compiler, but they don’t, at least not currently. Not in the sense that I defined it at the beginning of this post. What they do seem to have and call a quantum compiler are some subroutines that expand a single qubit gate with multiple controls attached into a sequence of single qubit rotations and CNOTs. But Qubiter has that already too. Look at its CktExpander.py file.

Duel Between Microsoft’s ProjectQ and Liqui|> software


December 1, 2016

Dumbing Down a Quantum Language, Sequel 1

Filed under: Uncategorized — rrtucci @ 8:04 pm

I am very happy to announce that I have added a class CktExpander to Qubiter At GitHub. The class reads any English file previously written by Qubiter and writes new English and Picture Files wherein every line of the original English file is expanded, if possible. A general Qubiter English file can have lines which denote U(2) matrices or swaps with 0, 1 or more controls attached. We say such a line is expanded if it is replaced by a sequence of lines each consisting of either (1) a qubit rotation or (2) a simple CNOT with only one control. Expander subroutines of this type are useful because quantum computers (for instance, IBM Quantum Experience) can only perform (1) or (2).

I have written a Jupyter Notebook that illustrates how to use this new Qubiter capability.

Actually, on June 2010, I published a blog post where I described a very similar effort: “Dumbing Down A Quantum Language“. Back then, I was using JAVA instead of Python. But afterwards, I came to the conclusion that JAVA support for numerics, linear algebra, plotting and statistics is inadequate for the purposes of writing Qubiter, whereas Python, with numpy, scipy, mathplotlib, pandas, etc., is almost perfect for the job. So when I was a java head, I wrote some classes that also expanded the lines of an English file into simpler operations. I am very happy that this is the second time that I try to write such subroutines, because practice makes perfect, even in programming. I feel that my Python expander subroutines are far better than my prior JAVA expander subroutines.

November 2, 2016

Benvenuti Tao Yin and Henry Tregillus

Filed under: Uncategorized — rrtucci @ 9:45 am

Benvenuti our newest interns, Tao Yin and Henry Tregillus. Tao Yin recently earned a PhD from Goethe University in Frankfurt, Germany. Henry Tregillus, who is close to obtaining a BS in Physics from Fort Lewis College, in Colorado, was one of our interns last summer and has promised to continue working for us. Tao and Henry are both working to improve and extend Quantum Fog.

An Evening of Quantum Crypto

Filed under: Uncategorized — rrtucci @ 9:30 am

The Toronto Quantum Computing Meetup is pleased to announce that our next meeting, to be held on Wed. Nov. 16, will be on the subject of Quantum Cryptography. Although strictly speaking, quantum crypto and quantum computing are different subjects, they are often lumped together. IQC at the University of Waterloo, Canada, has invested tons of money on quantum crypto. The US and Chinese governments have too. Ever wonder about the physics involved in quantum crypto or about its commercial prospects? If so, come to discuss this with our club members. The talk will be given by Sara Hosseini, who recently earned a PhD in quantum optics and quantum crypto from the Australian National University. Sara was an intern of artiste-qb.net in the past and she is a member of the meetup.

Toronto Quantum Computing Meetup doesn't disappoint

Toronto Quantum Computing Meetup doesn’t disappoint


October 30, 2016

Halloween Story: Beware the Super Boson Sampler, my son

Filed under: Uncategorized — rrtucci @ 2:28 am

Scary things seem to occur in the month of October, and even at the beginning of Nov, at least up to Nov. 8. Therefore, most years I write a special Halloween post for this blog to report on some of those things. This year, scary things have occurred in all areas of human endeavor (European and American politics, Syrian war, Zika, etc.). They have even occured in the area of quantum computing…One event of this kind that should be particularly vexing to all true Texan patriots is the imminent completion of the Super Boson Sampler.

The Super Boson Sampler, aka the Desertron, is a quantum computing TIME PORTAL device being built secretly by the NSA in Waxahachie Texas. The Director of the Desertron lab and original proponent of the device, Prof. Scott Aaronson of UT Austin, is being favorably compared to Robert Oppenheimer, director of the Los Alamos Laboratory during the Manhattan project.

Once it becomes operational before the end of this year, the Super Boson Sampler will be ten times more powerful than CERN’s Large Hadron Collider, another quantum computing time portal device, one that was designed as a precursor small scale toy model for the Super Boson Sampler.

Here is a picture, leaked to the press by a group that calls itself the Texan Freedom Fighters, of the Super Boson Sampler.


Rumor has it that the device is currently charging up, and that it will become fully operational one day after the American presidential election on Nov 8, probably with the intention of post-rigging the election in case things don’t work out for Hillary.

Here is one of many articles on the internet in which Prof. Aaronson explains his theory of time travel. According to that theory, the Super Boson Sampler will allow its users to travel backwards in time.

Quantum Aaronson Supremacy
is the belief held by some, including Aaronson himself, that the universe rotates around a fixed point called Computational Complexity Theory. Extended Quantum Aaronson Supremacy is the belief, also held by Aaronson, that that fixed point is Prof. Aaronson himself.

Recently Prof. Aaronson was flown to the White House, along with a large bunch of other highly placed quantum computing politicians, to give a very definitive FIVE MINUTE talk. I can see how that was a totally justifiable use of government resources. As Abraham Lincoln said: “Government of the rich elites, by the rich elites, for the rich elites, shall not perish from the Earth”.

Here is a small excerpt of his speech. We copy and pasted this excerpt from this blog post by Prof. Aaronson. Then our editor added the string ‘[Aaronson]’ in 2 places to facilitate comprehension by the reader. Prof. Aaronson is very confident that his ideas are golden. In fact, he is already comparing his achievements to the discovery of the Higgs Boson and the Fermi pile

If I have any policy advice, it’s this: recognize that a clear demonstration of quantum [Aaronson] supremacy is at least as big a deal as (say) the discovery of the Higgs boson. After this scientific milestone is achieved, I predict that the whole discussion of commercial applications of quantum computing will shift to a new plane, much like the Manhattan Project shifted to a new plane after Fermi built his pile under the Chicago stadium in 1942. In other words: at this point, the most “applied” thing to do might be to set applications aside temporarily, and just achieve this quantum [Aaronson] supremacy milestone—i.e., build the quantum computing Fermi pile—and thereby show the world that quantum computing speedups are a reality. Thank you.

October 12, 2016

Quantum Computing and Bayesian Networks for Global Monitoring of Pandemics

Filed under: Uncategorized — rrtucci @ 9:59 pm

Artiste-qb.net, the quantum computer software company that Henning Dekant and I co-founded recently, is very pleased to announce that we have started a collaboration with the Signa project, whose goal is to produce a universal platform for global monitoring of pandemics. Henning has written a beautiful blog post explaining the motivation behind the Signa Project. Signa is headed and is the brainchild of the multi-talented and visionary Andrew Deonarine, who will start postgraduate work at Harvard by the end of this month. Andrew has submitted a proposal to the MacArthur Foundation’s “$100M and Change” competition. If we don’t win EL Gordo, we will of course pursue other sources of funding. Andrew has prepared a YouTube video

of his vision, which will use as a starting point already existing software written by himself and many others, including our company, artiste-qb.net.

Here is a single frame from Andrew’s video showing the Signa Team so far.

September 20, 2016

In Love With Jupyter Notebooks, Post-Processing Your Lab Notebook

Filed under: Uncategorized — rrtucci @ 6:16 pm

I am pleased to announce on behalf of http://www.artiste-qb.net artiste-logothat our open source BSD licensed programs Qubiter and Quantum Fog now have some Jupyter Notebooks (JN’s), the first of hopefully many JN’s to come in the future. So far, Qubiter has 2 notebooks explaining Teleportation and the IBM Quantum Experience, whereas Quantum Fog has a notebook testing some ideas on how best to plot a quantum density matrix.

The way I see it, JN’s represent a method of using software that seems better suited for scientific investigations than the older method of “GUI (graphical user interface) rich” software.

Typically, GUI rich programs allow you to save some files with the fruits of your labor, but there are often several of those files, perhaps written in different formats, some human readable text formats and some propietary non-human readable ones. A JN, on the other hand, merges all those files into a single one that is stored in an open, very common, multimedia, browser readable format called JSON. The JN also records the commands that led to each of the files that are being merged plus it allows you to insert rich text comments between those files. All this makes JN’s, in my opinion, a much more unified, clear and complete way of documenting your thought process, both for yourself, and for others who might be interested in following your work.

Consider the lab or work notebooks of famous scientists (DaVinci, Darwin, Newton, Feynman, …). I for one find those brain storming and data recording documents endlessly fascinating and hope they continue to be written on paper and by hand till the end of humanity, but even those historic documents would have benefitted from some post-processing using the full panoply of modern computer tools now available to us. Imagine a Leonardo or a Darwin or a Feynman notebook with simulations and some plots and statistical analysis. Raw data can be post-processed using statistical packages. Thorny equations can be post-processed too, with symbolic manipulation programs, numeric algorithms programs and plotting programs. Such post-processing is what JN’s allow us to do.

The idea of writing software for creating such notebooks is not new. Although probably not the first software to use them, Wolfram’s Mathematica did much to popularize them. Even if you have never heard of JN’s, you probably have encountered Mathematica notebooks by now, wonderful multimedia files that can contain and execute Mathematica code, plots, animations, text with Latex equations embedded in it, etc. JN apps do all of that too, but they are open source under BSD license. They are much more adaptable to other platforms. They also rely more on browser and internet software resources (HTML, JavaScript, MathJax for LaTeX rendering, JSON format…) so they are ideally suited for an application running on the cloud, although they can also be run autonomously on a single PC.

JN’s were originally built as an app that ran on top of IPython, a command shell for Python, but the app has been carefully written so that it can be easily assimilated by other computer languages. 30 to 40 computer languages already have JN’s, including many languages that are not interpreted languages. Interpreted languages are languages like Python and Mathematica that are designed to run one line at a time.

Home of project Jupyter:

The original programmer of IPython and JN is Fernando Perez. Here is blog post by him describing JN history.

August 28, 2016

Toronto is Hosting a Galactic Jamboree: Quantum Computing from a Business Perspective

Filed under: Uncategorized — rrtucci @ 7:28 am

I’m proud to announce that the Toronto quantum computing meetup group will meet again on Sept 7 at a room that belongs to the Creative Destruction Lab, which is part of the Rotman Business School of the Univ. of Toronto. This meetup is being run by Henning Dekant (Henning and I recently founded a quantum computing software startup called artiste-qb.net).

We hope that this Sept 7 meeting, because it will be held at a business school venue, will encourage dialogue between technical and business people, the pocket protector and suit & tie wearers, with a common interest in quantum computing. And of course, rich investors, the Gucci shoe wearers, are welcome to this humble gathering too. If you are an entrepreneur who wants to start your own quantum computing company, or an investor mulling over investing in one, this meeting is a once in a lifetime opportunity for you.

Let me note that Silicon Valley also has a Quantum Computing meetup, but theirs is of inferior quality compared to the Toronto one. Their group probably loves Uber, the Silicon Valley based company with the worst customer support in the history of mankind, whereas Toronto has been in the forefront of curbing Uber. So you can see why the Toronto Quantum Computing meetup is far superior to the Silicon Valley one. In 200 years, George Bailey will become George Jetson and he’ll be flying down the road observing billboards such as this



August 14, 2016

Quantum Fog on the verge of becoming Sentient: it can now distinguish between (the words) “Good” and “Evil”

Filed under: Uncategorized — rrtucci @ 7:29 pm

midnigh-garden_good_evilYou have to start somewhere. First those 2 words, then … the Oxford Dictionary?

I am pleased to announce that I and http://www.artiste-qb.net have added a new, major addition to Quantum Fog. QFog can now learn classical (and quantum) Bayesian Networks from data fairly well by today’s standards.

As far as I am concerned, the gold standard for software that learns bnets from data is bnlearn, by Marco Scutari. To show my readers how the current Quantum Fog and the current bnlearn compare, I took a snapshot of a portion of the home page of http://www.bnlearn.com, the portion that enumerates the various algorithms that bnlearn can do, and I put a red check-mark next to those that QFog can now do too. As you can see, QFog is still behind bnlearn, but not by too much.


So why am I trying to replicate bnlearn, isn’t that silly? Because bnlearn is in R, whereas I want to write something in Python, using Pandas. Furthermore, I want to write a software library that allows you to analyze BOTH, classical and quantum bnets alongside each other.

Pandas is a Python library that replicates many of the statistical capabilities of R. R is super popular among statisticians, but Pandas, less than a decade old, has also received many plaudits from that community. The original author of Pandas, Wes McKinney, has written a wonderful book about Pandas, numpy and, more generally, about doing data science with Python.

There are very close ties between the R and Python communities, and it’s fairly easy to call R subroutines from Python and vice versa. Pandas was Wes McKinney’s love poem to R. In the future, I and http://www.artiste-qb.net are planning to use bnlearn subroutines often. At first, I’m sure that most bnlearn subroutines will perform better than those of Quantum Fog and that we can improve QFog a lot by comparing its performance, architecture, and output with that of bnlearn.

There are certain aspects of bnlearn that we haven’t replicated yet. For example, bnlearn does continuous (just Gaussian) bnets whereas we don’t yet. In the quantum case, Gaussian continuous distributions would entail coherent and squeezed coherent states. Let the LIGO people worry about that.

On the other had, at this point, QFog’s inference capabilities are better than those of bnlearn. QFog can do the message passing join tree algorithm and bnlearn can’t. (At present, bnlearn can do inference only using Monte Carlo)

And then there is the Judea Pearl do-calculus, both for classical and quantum bnets. Neither bnlearn nor QFog can do that yet, but some day soon… BayesiaLab is way ahead of everyone else in that regard. They already have a beautiful graphical implementation of the Judea Pearl do-calculus stuff for classical bnets.

Added later: Judea Pearl do-calculus has also been implemented in the following R package. Thanks to M.S. for telling me about this:

July 26, 2016

Toronti, la nuova Roma di computazione quantistica

Filed under: Uncategorized — rrtucci @ 6:40 am

Sono un principiante in Italiano, ma lo amo.

Toronto is Canada’s most populous city with 2.6 million people. It is a 1.5 hour drive from Waterloo, Canada, home of the IQC (Institute for Quantum Computing, a misnomer, should be Institute for Quantum Cryptography) and PI (Perimeter Institute, where Justin Trudeau works). The University of Toronto, Canada’s largest university, is well known for its expertise in AI and Bayesian networks too. Geoffrey Hinton, a famous Deep Learning, Neural Networks researcher, worked at the Univ. of Toronto before he was hired by Google in 2013. Also, IBM, a mayor competitor in the race to build a gate model qc, has substantial research facilities in the Toronto area.

Henning Dekant (in Toronto) and I (in Boston) recently started a quantum computer software company called artiste-qb.net (our company logo artiste-logo)

I am writing this blog post to announce that

  • artiste-qb.net is now hiring 2 student interns (at almost minimum wage, sorry) to write software, open source of course
  • Henning is starting a quantum computing Meetup in Toronto

    Quantum Computing and Data Science

    Toronto, ON
    1 Members

    The future of computing has come out of the labs. Software development for quantum computing is happening in the GTA, and this meetup aims at bringing people from this fledgli…

    Check out this Meetup Group →

Some say the most powerful weapon in the Galaxy is the Death Star, but this is better.

July 14, 2016

Quantum Fog, a quantum computer simulator based on quantum Bayesian networks, can now Think (at least better than a rock)

Filed under: Uncategorized — rrtucci @ 6:51 pm

Today, I added a folder called “learning” to Quantum Fog. QFog is a quantum computer simulator based on Bayesian Networks (bnets). Classical Bayesian networks are what earned Judea Pearl a Turing Prize. Quantum Fog implements seamlessly both classical Bayesian networks and their quantum generalization, quantum Bayesian networks.

The way I see it, the field of classical Bayesian networks has had 2 Springs.

The first Spring was about 20 years ago and it was motivated by the discovery of the join tree message passing algo which decreased significantly the complexity of doing inference with bnets. That complexity is exponential regardless, but the join tree algo makes it exponential in the size of the largest clique of the graph.

The second Spring is occurring right now, and it is motivated by the discovery of various algorithms for learning bnets by computer from the data. Immediately after the first Spring, bnet inference could be done fairly quickly, but the bnet had to be divined manually by the user, a formidable task for bnets with more than a handful of nodes. But nowadays, that situation has improved considerably, as you can see by looking at my 2 favorite open source libraries for learning bnets from data:

  1. bnlearn. Very polished, R language. Written by Marco Scutari
  2. neuroBN, a less polished but very pedagogically helpful to me. Python language. Written by Nicholas Cullen

Its new ”learning” folder gives Quantum Fog a rudimentary capability for learning both classical bnets and quantum bnets from data.(so far QFog can only do Naive Bayes and Chow Liu Tree algos. Soon will add Hill Climbing, Tabu, GrowShrink, IAMB and PC algos) Previous workers like Scutari and Cullen only consider cbnets. Quantum Fog aims to cover both cbnets and qbnets seamlessly. We hope QFog can eventually generate ”programs” (instruction sequences) that can be run on real quantum computer hardware.

Quantum Fog goes to pet school


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