# Quantum Bayesian Networks

## 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).

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.

## 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 that 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: http://jupyter.org The original programmer of IPython and JN is Fernando Perez. Here is blog post by him describing JN history. http://blog.fperez.org/2012/01/ipython-notebook-historical.html ## 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 You 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: https://cran.r-project.org/web/packages/pcalg/index.html ## 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 ) 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… 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 ## June 24, 2016 ### Qubiter’s Excellent Adventure, an Out of Body Quantum Experience with IBM Filed under: Uncategorized — rrtucci @ 9:20 pm On the first week of May, 2016, IBM released, to much fanfare, on the cloud access to a 5 qubit, gate model quantum computer. And with a very nice graphical interface and accompanying simulator to boot, so you can compare the experimental results to the theoretical ones (neglecting noise). They call their service “Quantum Experience” (QE as in Queen Elizabeth, very pro British). You can join QE and use it yourself here The service is free and available to everyone. I haven’t been blogging too much lately because I’ve very been busy programming my newest project and raising Cain with my silly jokes on Twitter, but it would be a crime if I didn’t write something about this historic for quantum computing release. So here we go. Much has been written about QE already. Some “experimental” papers have been submitted to arXiv (for example, https://arxiv.org/abs/1605.04220 https://arxiv.org/abs/1605.05709 https://arxiv.org/abs/1605.08922 https://arxiv.org/abs/1511.00267 ). Not exactly Fermi caliber experiments, but certainly fun and educational to some. Also, some programmers have written their own simulators and put them on github (for example, Ganesh, Corbett, Bengualid, and many others) As my own contribution to all this lively, welcomed activity, I uploaded to Qubiter’s github repo The script illustrates how to use Qubiter to simulate QE. It outputs for a simple quantum circuit that uses all the gates and only the gates currently realizable by QE. The script also writes on the Python console the probabilities of each of the 5 qubits at the end of the evolution specified by the given initial state vector and quantum circuit. Of course, Qubiter is capable of simulating much more complicated quantum circuits. This is like a “Hello World” exercise for it. Qubiter is so powerful that it is already capable of simulating the Matrix v0.01. Okay, I’m exaggerating just a little bit. At present, Qubiter can do quantum Fourier transforms, quantum phase estimation, and quantum chemistry (finding ground state energies of simple molecules) ## June 8, 2016 ### Microsoft Quantum Computing Software Patents, A Watch Page Filed under: Uncategorized — rrtucci @ 6:21 am This blog post will be dedicated to posting links to Microsoft quantum computing software patents. I will keep adding to it as I become aware of newer patents. My method of finding patents is to use the USPTO search engine for granted patents with the queries: AN/Microsoft AND IN/Wecker AN/Microsoft AND IN/Svore Note that the USPTO also has a search engine for patent applications that are not yet granted. I am not listing those here. You can use that search engine yourself if you also want to see “Previews of the Coming Attractions” I give patent links to the GooglePatents website (instead of to the USPTO website) 1. Quantum gate optimizations https://patents.google.com/patent/US9064067B2/en 2. Optimizing quantum simulations by intelligent permutation https://patents.google.com/patent/US8972237B2/en 3. Language integration via function redirection https://patents.google.com/patent/US9292304B2/en 4. Quantum annealing simulator https://patents.google.com/patent/US9152746B2/en 5. Fast quantum and classical phase estimation https://patents.google.com/patent/US9275011B2/en 6. Method and system that produces non-stabilizer quantum states that are used in various quantum circuits and systems https://patents.google.com/patent/US9269052B2/en 7. Method and system for optimal decomposition of single-qubit quantum circuits using standard quantum gates https://patents.google.com/patent/US9208280B2/en ## May 28, 2016 ### Don’t tell Microsoft. Qubiter, an open source platform, can now do quantum chemistry too Filed under: Uncategorized — rrtucci @ 8:10 pm I’ve uploaded to https://github.com/rrtucci/my-chemistry a small collection of classes called my-chemistry’ that allow one to construct a gate model quantum circuit for calculating the ground state energy of molecules using Kitaev’s Phase Estimation Algorithm. Notice that I am releasing my-chemistry under my name only. Although this is an add-on to the artiste-qb.net Qubiter project, the Artiste company is free of any legal liability, as I have not merged it with the main code branch, and the company is not deriving any use of it at this time. The docstrings of each class describe in detail how it works. All my classes have a main method at the end with examples and tests of the class. In addition, I have written a pdf document describing the more technical details of the quantum circuit involved. The pdf document is part of the my-chemistry distribution. Here is an excerpt from the Introduction section of that pdf document: This paper describes the particular circuit used by a Python software package called “my-chemistry”, written by R.R.Tucci, and available at GitHub, Ref.[1]. The software can be used in conjunction with “Qubiter”, another Python software package available at GitHub, Ref.[2]. A quantum circuit that is very similar to the one presented in this paper has previously been implemented FIRST in Ref.[4] and more recently and exhaustively in the closed source software package called Liqui$|\rangle$ produced by Microsoft, with Dave Wecker as main author. Here is a super brief, by no means exhaustive review of some of the highlights in the history of this quantum computing approach to chemistry. The person deserving the lion share of the credit for this method is A. Kitaev, who in 1995, Ref.[3], was the first to propose the PEA. Also very deserving are Trotter for his expansion, and Jordan/Wigner for their transformation. The first paper to present an actual computer program for calculating the ground state energy of an$H_2\$ molecule using PEA appears to be Ref.[4], by Whitfield, Biamonte and Aspuru-Guzik.

Researchers working for Microsoft applied the method to more complicated molecules and found some very clever optimization methods, such as using the identity $(CNOT)^2 = 1$. Here is their epiphany paper Ref.[5], and here is their most recent paper Ref.[6]. The latter is recommended for what appears to be a very fair and exhaustive list of references of this approach.

Finally, one should mention that Microsoft has several patents on this method, so it is possible that Microsoft will claim in the future that the software described in this paper infringes on one of their patents. Going to the USPTO website and using the query IN/wecker AND AN/Microsoft`, I located 4 patents Refs.[7][8][9][10] on Liqui$|\rangle$. There might be more pending.

Patents alluded to

Quantum gate optimizations

Optimizing quantum simulations by intelligent permutation

Language integration via function redirection

Quantum annealing simulator

## April 8, 2016

### Moral Corruption of Krysta Svore and Her Accomplices

Filed under: Uncategorized — rrtucci @ 3:09 am

Check out the following paper by Krysta Svore from Microsoft and her accomplices:

A Software Methodology for Compiling Quantum Programs, by Thomas Häner(1), Damian S. Steiger(1), Krysta Svore(2), Matthias Troyer(1,2,3)

1. Theoretische Physik, ETH Zurich, 8093 Zurich, Switzerland
2. Quantum Architectures and Computation Group, Microsoft Research, Redmond, WA (USA)
3. Microsoft Research Station Q, Santa Barbara, CA (USA)

excerpt from paper:

Related Work.
One of the earliest proposals for a scalable software methodology for quantum compiling dates back a decade [12] and presents significant steps of any quantum computing design flow. Our work expands upon this work, extending the stack elements by showing how to integrate, e.g., tuned quantum libraries of arithmetic, subroutines, and quantum gates, and providing concrete details of the compilers and optimizers in the stack

[12] Krysta M Svore, Alfred V Aho, Andrew W Cross, Isaac Chuang, and Igor L Markov, “A layered software architecture for quantum computing design tools,” Computer, 74-83 (2006).

Now look at this

Krysta is such an unethical, despicable liar, she should be running for president of the United States or president of FIFA. Her new paper has 33 references but she doesn’t mention my quantum compiler papers and Qubiter software, even though they have the words Quantum Compiler explicitly in the title and they started in 1999, seven years before her clumsy, copy-cat efforts. (Note that her 2006 paper doesn’t mention my 1999 paper and software either. She has been lying for 10 years.)

Don’t trust anything Krysta SNORE tells you. Some call her Quantum Carly Fiorina, some compare her to a female praying mantis or a snake. Microsoft’s quantum software is closed source which is anti-thetical to academic work. Join quantum open source today.

## March 31, 2016

### MIT Stunned by Scalable Quantum Computer

Filed under: Uncategorized — rrtucci @ 11:16 pm

Okay, I don’t expect any of my readers to believe me, but I have a Martian WiFi wormhole connection which allows me to access the Internet in the future. Today, I came upon this article that will be published exactly 15 years in the future.

MIT Stunned by Scalable Quantum Computer
April 1, 2031. MIT Tech Review

A team of scientists from MIT led by Prof. (also Dean of MIT Physics Dept., and chief editor of Physical Review) Isaac Chuang has just published a paper in Physical Review that describes how they used a 5 qubit quantum computer built of superconductive Niobium rings called SQUIDs to show that 15 =3×5.

Those of us who are old enough to remember may recall that MIT was the first to show in 2001 that 15=3×5 with an NMR quantum computer.

Then, MIT scientists stunned themselves with their brilliance once again when 15 years later, in 2016, they were the first to show 15=3×5 with an ion trap quantum computer.

And now, 15 years later, in 2031, MIT scientists were stunned once again, as if by a lightning out of the blue, when they managed against all odds to show that 15=3×5 with a superconductive quantum computer.

All 3 times that MIT has shown that 15=3×5, they have claimed that their device is scalable. We are beginning to believe them, but then again, in 2031, we are now so old that some days we can’t readily recall the current US president’s name.

Back in 2016, when Prof. Chuang was asked why he wasn’t comparing his ion-trap device to those of David Wineland’s team (at NIST, Colorado), and Chris Monroe’s team (at U. Of Maryland), Prof. Chuang pointed out that those people’s devices were so different to his that he was totally unaware of their existence. According to Prof. Chuang, his device was placed in a lab-room with green colored walls, whereas Wineland and Monroe had used beige colored walls. According to a powerful theorem by Prof. John Preskill of Caltech, the boundary conditions (in this case the color of the lab-room walls) affects so much the evolution of the bulk (in this case the device), that quantum devices placed in lab-rooms with green and beige colored walls behave so differently that they are incomparable. Or so Chuang claims.

Today, April 1, 2031, Prof. Chuang was asked why he isn’t comparing his 5 qubit superconductive device to the 100 qubit superconductive devices built by Google and IBM last year. Once again, Prof. Chuang defers to Preskill’s Theorem which proves those devices are incomparable to his.

Prof. Chuang delivers Commencement speech at MIT

Coed hen at MIT 2031 graduation ceremonies very impressed by Prof. Chuang’s pronouncements

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