# Quantum Bayesian Networks

## July 30, 2019

### Quantum Computing Patents for sale

Filed under: Uncategorized — rrtucci @ 11:53 am

I have 4 quantum computing patents to my name that I am looking to sell for cash. They are described here. If interested, contact me at rrtucci_at_gmail.com or at the email address given on the right margin of this blog. I am also available for consulting on quantum computing patents, about which I have intimate knowledge accrued over many years.

## April 30, 2019

### Leaving artiste-qb.net

Filed under: Uncategorized — rrtucci @ 3:06 am

After working for 5 years at artiste-qb.net, I am leaving that company for personal reasons. I am looking for a new job. I would prefer to have a job doing what I love, quantum computing software and algorithm development, but I am open to other kinds of job offers as well. I am proud to be the almost sole developer of Qubiter and Quantum Fog, two insanely great software libraries. I believe that Qubiter, with its new addition for calculating gradients of quantum cost functions, will become a seminal work in the field. I also have an unpublished but very mature library for doing quantum entanglement calculations that is also insanely great. I write software so that it will last forever 💍💍💎💎

Write software that will save the world, not eat it 🙃 You can’t save the world and eat it too🍕🌮🍧

## September 8, 2019

### Jeffrey Epstein and Seth Loyd

Filed under: Uncategorized — rrtucci @ 5:01 am

Not sure why it shows [removed], but the whole story can be found if you click on the Reddit link below

Turns out that the moderator of the Quantum Computing Reddit has chosen to protect the pedophilia enabler Seth Lloyd by removing the very civilized thread that I initiated. Here is another Reddit thread on the same topic.

## September 5, 2019

### IBM releases first free quantum computer programming textbook/course completely based on jupyter notebooks

Filed under: Uncategorized — rrtucci @ 3:24 pm

I’ve frequently advocated in this blog for the use of jupyter notebooks. I think it’s a great idea to release, as IBM has done today, a free quantum computer programming textbook completely based on jupyter notebooks. I see this as a natural evolution from the clunky programming manuals of the 20th century. This IBM textbook makes a recent crop of quantum computing paper textbooks suddenly seem obsolete and expensive. It’s probably also the last nail in the coffin of Microsoft’s Quantum Katas — another dud in a long line of poorly conceived and profoundly unpopular Microsoft products. IBM probably wrote this textbook prompted in no small measure by the MS Katas, and it quite effectively counteracts and nullifies them, because IBM has their own qc hardware to invoke in their textbook, and MS doesn’t.

## August 28, 2019

### I have a Dream, Stardust

Filed under: Uncategorized — rrtucci @ 3:14 pm

## August 21, 2019

### Topologically protected state implemented with squids by Chinese group from Tsinghua Uni.

Filed under: Uncategorized — rrtucci @ 10:14 pm

https://physics.aps.org/synopsis-for/10.1103/PhysRevLett.123.080501

## August 17, 2019

### Brendan Eich And SMBC comics voice their opinion on some quantum startups

Filed under: Uncategorized — rrtucci @ 2:40 pm

## August 11, 2019

### Day One of quantum-bnlearn

Filed under: Uncategorized — rrtucci @ 5:50 pm

I’ve sung the praises of bnlearn in this blog many times before.

bnlearn is an R package for structure learning of bayesian networks. (Note, however, that it is very easy and painless to call C from R, and all the time consuming parts of bnlearn, more than half of its code lines, are written in C. Also, in case you prefer python to R, a python wrapper for bnlearn is in the works. Until that wrapper comes out, R-magic allows you to call bnlearn in R within a python jupyter notebook. In fact, I do this in the jupyter notebooks of my program Quantum Fog.)

bnlearn is the labor of love, ten years in the making and still going strong, of the kind, smart, wise Marco Scutari.

I am sure that most of the stuff in bnlearn has a quantum bayesian networks analogue and will someday be part of what is nowadays being called in quantum computing circles, quantum ai. Whether quantum bnlearn will be useful for anything, or better in any way to its classical counterpart, God only knows, but it certainly will be different and interesting to explore. Let this blog post mark the first day of quantum bnlearn, which I will henceforth call Project Scutari, in honor of this great man.

## August 5, 2019

### Nitwit mansplains quantum computing to Sabine Hossenfelder

Filed under: Uncategorized — rrtucci @ 2:30 am

I reported on Reddit about Sabine’s article and got -17 ratings on two of my comments. A badge of honor in this case. I think that such a strong reaction against Sabine’s mild article and my comments shows that we hit a raw nerve, or hit close enough to one to cause sharp pain. Often, when you criticize someone, those to whom the criticism applies display their true colors in their response to that criticism. This has been the case in the response to Sabine’s article, on Reddit and on Twitter. I won’t get more specific than that. I leave it up to you to interpret this whole affair if it concerns you.

## August 2, 2019

### Quantum Ghosts, not

Filed under: Uncategorized — rrtucci @ 5:41 am

Check out

Quantum Ghosts by Catherine Klauss

The article reports that a group of Israeli programmers has added to IBM qiskit a simulator that stores a state vector for each possibility (“branch”) of a measurement. The article implies that this Israeli-qiskit simulator is the first to have this feature, but Qubiter has had this feature for 4 years. For example, Qubiter uses this feature in its notebook explaining Teleportation

https://nbviewer.jupyter.org/github/artiste-qb-net/qubiter/blob/master/qubiter/jupyter_notebooks/Teleportation-showcasing-IF_M-blocks.ipynb

The article also implies that this feature is equivalent to the Everett multi-world interpretation of quantum mechanics. Not true. This is just a computational device. You don’t have to believe in multiple worlds to use this computational device. In fact, an analogous computational device exists in classical probability, and one doesn’t have believe in multiple worlds to use that either.

## July 30, 2019

### Speeding Up Python

Filed under: Uncategorized — rrtucci @ 10:18 am

“Use Cython to get more than 30X speedup on your Python code” by George Seif https://link.medium.com/GkeRZLl3JY

## July 2, 2019

### Qubiter now has an automatically generated SUMMARY of all its Jupyter notebooks

Filed under: Uncategorized — rrtucci @ 7:36 pm

I just added to Qubiter one of those features that Americans like to call “A Big Time Saver”. Automobiles, washers and driers of clothing, those are all big time savers, but this is even better… for Qubiter users.

Something about Qubiter’s jupyter_notebooks folder had been embittering my life. But, praise the Lord and Hallelujah :), today I found a solution to that something, a solution that I find very satisfying. Let me tell you all about it.

Qubiter has a folder full of Jupyter notebooks (in fact, 27 of them). Opening a notebook takes a short while, which is slightly annoying. I wanted to give Qubiter users the ability to peek inside all the notebooks at once, without having to open all of them. Qubiter’s new SUMMARY.ipynb notebook allows the user to do just that.

SUMMARY.ipynb scans the directory in which it lives to find all Jupyter notebooks (other than itself) in that directory. It then prints for every notebook it finds (1) a hyperlink to the notebook, and (2) the first cell (which is always markdown) of the notebook. This way you can read a nice, automatically generated summary of all the notebooks without having to open all of them. If you find a notebook that you want to explore further, you can simply click on its link to open it.

Here is the code that I use. I posted it on StackOverflow

https://stackoverflow.com/questions/56829884/how-to-execute-cell-1-from-another-notebook-in-current-notebook?noredirect=1#comment100244813_56829884

And here is Qubiter’s notebook using the code:

https://nbviewer.jupyter.org/github/artiste-qb-net/qubiter/blob/master/qubiter/jupyter_notebooks/SUMMARY.ipynb

## July 1, 2019

Filed under: Uncategorized — rrtucci @ 4:39 pm

P.S. Xanadu AI is a scam Canadian company that has nothing to do with “Project Xanadu” of the brilliant Ted Nelson.

## June 30, 2019

### A Cool, Highly Effective Combination: parametric quantum circuit + Jupyter notebook with widgets + Qubiter

Filed under: Uncategorized — rrtucci @ 3:08 am

Check out my new Jupyter notebook for Qubiter.

Sorry. The following link was broken for a while because I unwittingly damaged the json format of the notebook. It’s now working again

Here is a jpeg of the widgets that this notebook presents to the user. On my computer, it takes a few seconds before the widgets are rendered, so if you don’t see this immediately, near the bottom of the notebook, when you open the notebook in your browser, just be patient. Sometimes, the widgets don’t show up unless you **run** the notebook. Sorry.

Suppose that you are interested in printing out the state vector of a quantum circuit at various times (points) in its evolution, as well as at the end of the circuit. Qubiter can do that.

Furthermore, suppose that the circuit is a parametric one, and you want to vary its parameters using sliders on a gui (graphical user interface). Qubiter can do that too, via a jupyter notebook with widgets. This notebook is one such notebook.

A jupyter notebook with widgets gives you the best of both worlds, the gui world and the notebooks world.

Gui’s excel at reducing the possibility of user errors, increasing the ease of use for the user, and reducing the amount of understanding of the code that is demanded from the user in order for him or her to use the code correctly.

Notebooks excel at providing a robust, flexible, ready made, familiar method of documenting and saving your work for multiple use cases. They are also great for explaining your work to others with great detail and precision.

## June 29, 2019

### Xanadu AI, Canadian Quantum Computing Ponzi scheme, gets an extra CAN$32 Million Filed under: Uncategorized — rrtucci @ 12:38 pm In a previous blog post, I commented about Xanadu AI: The latest news about the Xanadu Ponzi scheme is that they just got an extra CAN$32 Million (This raises their total funding so far to CAN\$41M, according to TechCruch). This company has practically zero chance of succeeding. Their quantum computing technology, using squeezed light, is **far inferior** to the ones (ion trap, squids, optical, anyons, quantum dots) being pursued by a crowded field of well funded startups (Rigetti, IonQ, PsiQ, and many others) and giant monopolies (IBM, Google, Microsoft, Intel, Alibaba, Huawei, …).

The latest 32 million was reported in the Globe and Mail:

Excerpts in boldface:

But Xanadu needs to take “three giant steps,” before it can fully commercialize its technology, said Massachusetts Institute of Technology mechanical engineering and physics professor Seth Lloyd, a leading expert in quantum computing who advises the startup:

“They need to improve the squeezing by a significant amount and show they can get many pulses of this squeezed light into their device, and then control these pulses … [then] show you can actually do something that’s useful to people with the device. Given what they’re trying to do, they’re on schedule. Any one of those things could fail, which is the nature of science and life and being a startup.”

Only that, just a cake walk away. Right on schedule?? Squeezed light was invented by H. P. Yuen in 1976, 43 years ago. Brilliant experimentalists like Bernard Yurke and Jeffrey Kimble soon hit a brick wall in the amount of possible squeezing attainable. I hardly think that the CEO of Xanadu, Elizabeth Holmes or whatever his name is, can improve much on what they did. Nowadays, squeezing is used mainly by the LIGO people. I believe it might reduce their noise by a factor of 10 or so, but is that enough for Xanadu’s speculative analog quantum computer to perform calculations better than a cell phone. Highly doubtful.

The only thing that is on schedule here is Seth Lloyd’s Ponzi scheme.

Xanadu is looking to generate revenue in the short term with proof-of-concept projects for a few customers including Bank of Montreal, and by offering cloud-based software that customers can use to test out not only its quantum technology, but that of its competitors. Lawrence Wan, chief architect and head of enterprise platforms with BMO, said Xanadu’s approach “looks to be more commercially viable and scalable” than others.

Obvious BS. Why would the competitors with qc machines allow Xanadu to poach their clients? Besides, Xanadu’s underperforming or nonexistent squeezed light “quantum computer” is very different from a gate model machine so Xanadu is not especially qualified to advise others about gate model machines. Dozens of companies are already offering qc consulting services. Consulting won’t generate enough near-term revenue for Xanadu in the next 5-10 years of toy qc machines to cover the cost of the very expensive hardware R&D effort that they are “promising” to undertake.

Let’s face it, the real revenue maker for Xanadu is their Ponzi scheme.

## June 27, 2019

### Comments on quant-ph arXiv:1906.10726, “Quantum Causal Models”, by Jonathan Barrett, Robin Lorenz, Ognyan Oreshkov

Filed under: Uncategorized — rrtucci @ 6:59 am

The paper

“Quantum Causal Models”, by Jonathan Barrett, Robin Lorenz, Ognyan Oreshkov, https://arxiv.org/abs/1906.10726

was published by BLO tonight. This is my initial response to it.

It’s been just a few hours since BLO published this paper in arxiv, so I haven’t had a chance to read it in its entirety, yet. I have never communicated with BLO, so this is the first time the authors will hear about my response to it. However, much of the material covered in the BLO paper is familiar territory to me, having worked on QB Nets (Quantum Bayesian Networks) since my first paper on them in 1995

Excellent job! And it mentions my work. Thank you!

Here is how BLO explain the relevance of my work to theirs:

Many works are explicitly concerned with causal structure, but not to the end of a quantum generalization of causal models. These include, for example, Refs. [19, 22, 45, 64–69], and are not discussed here any further. Early work by Tucci [6, 7] aims at a quantum generalization of classical Bayesian (rather than causal) networks, obtained by associating probability amplitudes with nodes. More closely related to our work is that of Leifer and Poulin [9], which presents (amongst other things) an approach to quantum Bayesian networks, wherein a quantum state is associated with a DAG, and must satisfy independence relationships formalised by the quantum mutual information, given by the structure of the DAG. The results of Ref. [9] have at various times been used in our proofs. Leifer and Spekkens [11] adapt the ideas of Ref. [9] to quantum causal models, using a particular definition of a quantum conditional state. Our approach differs from that of Ref. [11] in taking influence in unitary transformations as defining of causal relations, in its use of the process operator formalism, and in the fact that we don’t use quantum conditional states.

Under Refs. 6, 7 they list

[6] R. R. Tucci, “Quantum bayesian nets,” International Journal of Modern Physics B 9 no. 03, (1995) 295–337.
[7] R. R. Tucci, “Factorization of quantum density matrices according to bayesian and markov networks,” arXiv:quant-ph/0701201.

I do disagree with their characterization of my work. My early work Ref.6 in 1995 was on QB nets for pure states, but then I published Ref.7 in 2007 which explains how QB nets can also be used to describe density matrices that are not pure states. In 2012, I published the following introductory review and reprise of the use of QB nets to describe general density matrices

“An Introduction to Quantum Bayesian Networks for Mixed States”, by Robert R. Tucci, https://arxiv.org/abs/1204.1550

I contend that what the BLO paper proposes is **exactly** QB nets for density matrices. They just call them by a different name. A rose by any other name would smell as sweet.

I have also published in this blog the following article describing the connection of QB Nets to “Tensor Networks”. This is an obvious connection that a lot of people have asked me about, and which is not addressed anywhere in the BLO paper. (I searched the BLO paper in vain for the phrase “tensor network”).

As an aside, I think that BLO’s Ref.9 by Leifer and Poulin is patently incorrect because it is based on a new definition of conditional density matrices which imposes major constraints on standard Quantum Mechanics. So, if the work of Leifer and Poulin applies to the real world at all, it does so only within the context of a severely maimed Quantum Mechanics.

QB nets, which are exactly what BLO call “Quantum Causal Models”, do not assume any axioms beyond those of standard Quantum Mechanics. QB nets are simply a graphical way of displaying (any, all) quantum density matrices, the same way that classical Bayesian networks are simply a graphical way of displaying (any, all) joint probability distributions. In the same way that classical Bayesian networks arise from the chain rule for joint probability distributions, QB nets arise from a chain rule for quantum **probability amplitudes**. That is the gist of Ref.7, cited by the BLO paper.

I would also like to point out that the BLO paper does not mention that I too have addressed Judea Pearl’s d-separation and do-calculus as it pertains to the quantum realm. In the 2013 paper:

“An Information Theoretic Measure of Judea Pearl’s Identifiability and Causal Influence”, by Robert R. Tucci, https://arxiv.org/abs/1307.5837

I address the do-calculus for **classical** Bayesian networks, but I do so in terms of entropy. I explicitly mention in the introduction to that paper, that I intentionally use only entropy concepts to define things, with the intention that these concepts be generalized to Quantum Mechanics, using the simple rule of replacing H(P) by S(\rho) (i.e., by replacing entropies of classical probability distributions by entropies of quantum density matrices). This “minimal substitution” was invented by Cerf and Adami, and has been proven to be a powerful guiding principle in Quantum Information Theory. For instance, it led me to the discovery of the definition of Squashed Entanglement, as documented in its Wikipedia article.

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