Quantum Bayesian Networks

November 30, 2020

My Free Open Source Book “Bayesuvius” on Bayesian Networks

Filed under: Uncategorized — rrtucci @ 3:08 pm


See also “Famous uses of Bayesian Networks

June 27, 2020

My Pinned Tweet at Twitter

Filed under: Uncategorized — rrtucci @ 9:28 pm

This is the pinned Tweet on my company’s (www.ar-tiste.xyz) Twitter account

March 2, 2021

How the Obama Presidential Campaigns Used Uplift Modelling (a subset of Causal Inference) to trounce the Republicans

Filed under: Uncategorized — rrtucci @ 7:13 pm

I am currently writing a chapter about “Uplift Modelling” (UM) for my free, open source book “Bayesuvius” about Bayesian Networks.

UM is a small subset of Causal Inference that has become a standard tool in the advertisement world. This is evinced by the fact that two great UM open source software libraries, CausalML (by Uber) and PyLift (by the e-commerce retailer Wayfair) , were written by e-businesses for advertisement purposes.

UM was also used very successfully during the Obama Presidential campaigns. In a nutshell, here is how UM was used by team Obama:

Suppose d=U for the untreated group (aka control group) and d=T for the treated group, where an individual is said to be treated if he/she is sent an email advocating climate change legislation.

Suppose that before and after the climate change email is sent out, the members of both the treated and control groups, are asked how important they rate the issue of climate change. For d=U,T, let y_d=1 if the individual rates the issue as important, and y_d=0 if not.


We can separate the population into 4 disjoint subsets, as shown in the above figure. Once the subset of Persuadables is identified, the lion share of campaign resources is targeted towards convincing that subset of the population to vote for Obama.

February 18, 2021

Comic strip of Caltech physicist working on qc

Filed under: Uncategorized — rrtucci @ 4:01 pm


Okay. I am being grossly unfair in the title. Many physicists outside Caltech are assholes too.

February 15, 2021

“Causal Inference for The Brave and True” book by Matheus Facure Alves

Filed under: Uncategorized — rrtucci @ 3:39 pm

Cover image of the new book “Causal Inference for the Brave and True”, by Matheus Facure Alves.

Wow Hollywood, did the Spartans really go to battle dressed in their speedos and a cape? And who is the movie star and handsome stud in the center?

I recently put out the word on Twitter that I was trying to understand the topic of “Synthetic Controls”, and pleading to everyone to recommend their favorite pedagogical reference on the subject. One gracious soul recommended the chapter on Synthetic Controls in the following book:

“Causal Inference for The Brave and True” by Matheus Facure Alves

I was hitherto unacquainted with this book. I like it very much. It seems to be another free, online, causality-themed, Covid-year, labor-of-love book like my Bayesuvius and Scott Cunningham’s mixtape book. Alves is an economist like Cunningham, and their books cover similar topics. Unlike my book, which contains no computer code, Cunningham’s and Alves’s books have an abundance of wonderful code examples. Cunningham uses R and Stata, whereas Alves uses Python, so they complement each other well in that respect.

According to Matheus’s Linkedin page, he is a Brazilian economist/data scientist, and currently the lead data scientist at Nubank. According to the Wikipedia entry for Nubank, “Nubank is a Brazilian neobank and the largest Fintech in Latin America. Its headquarters are located in São Paulo, Brazil…Altogether, Nubank has over 10 million customers in Brazil.” (population of Brazil, about 210M, in 2021)

Lest anyone in the financial services industries think that Causal Inference (a subset of Bayesian Networks) has little to contribute to their trade, here is a person who, like me, would vehemently disagree: Excerpt from his website

Eventually, all that studying paid off and I landed a job at a rising fintech. Finally, I could dedicate all my time to squeezing the last drop of predictive performance out of my models. It took me about a year to realize something wasn’t quite right. I had very performatic models and yet, they weren’t as useful as I thought they would be. Sure, I could predict what would happen to a customer or what would be next month’s marketing metrics. But that was all rather passive. I couldn’t influence the results in the direction that I wanted.

If you too are looking for an extra je-ne-sais-quoi from Data Science, maybe Causal Inference is the answer you seek.

I’m a big fan of the 2 minute papers guy. To quote him: “Hold on to your papers. Wow, what a great time to be alive!”.

February 12, 2021

TUDelft Quantum Computing Fraud

Filed under: Uncategorized — rrtucci @ 6:13 pm


Check out

Microsoft’s Big Win in Quantum Computing Was an ‘Error’ After All (WIRED, 02.12.2021 ) 


IN MARCH 2018, Dutch physicist and Microsoft employee Leo Kouwenhoven published headline-grabbing new evidence that he had observed an elusive particle called a Majorana fermion.

Three years later, Microsoft’s 2018 physics fillip has fizzled. Late last month, Kouwenhoven and his 21 coauthors released a new paper including more data from their experiments. It concludes that they did not find the prized particle after all. An attached note from the authors said the original paper, in the prestigious journal Nature, would be retracted, citing “technical errors.”

Two physicists in the field say extra data Kouwenhoven’s group provided them after they questioned the 2018 results shows the team had originally excluded data points that undermined its news-making claims. “I don’t know for sure what was in their heads,” says Sergey Frolov, a professor at the University of Pittsburgh, “but they skipped some data that contradicts directly what was in the paper. From the fuller data, there’s no doubt that there’s no Majorana.”

Sergey Frolov @spinespresso·

The authors later told us it was done for aesthetics. We have a problem with this.

For me, the importance of this story is not in telling us whether Majorana particles exist or not, or, more generally, whether quantum computing will ever be commercially successful or not. It will take many years before those issues are settled conclusively.

For me, the importance of this story is that it is a clear case of fraud. And it doesn’t surprise me. In my experience, the academic qc community is quite unethical, dishonest and amoral. It has kept this fraud secret for 3 years. It condones that Seth Lloyd, a proven Jeffrey Epstein enabler, still continues to be a professor at MIT, and continues receiving gov grants approved by the qc community. It condones that the tensor network crooked politicians (at Caltech, Simons Foundation and Google) have plagiarized Quantum Bayesian Networks. I could mention many other examples of their unethical or dishonest or amoral behavior, but what is the use. Here is an accurate movie portrayal of a typical academic qc expert at Caltech or MIT (my alma mater).

You can call me names and say I’m being sanctimonious. I don’t care, because I truly believe that scientists have a super-special obligation to behave ethically and honestly. As Spidey would say: “With great power comes great responsibility”. For me, Richard Feynman put it best in his 1974 commencement address at Caltech

the first principle is that you must not fool yourself, and you are the easiest person to fool

I would like to add something that’s not essential to the science, but something I kind of believe, which is that you should not fool the laymen when you’re talking as a scientist. . . . I’m talking about a specific, extra type of integrity that is not lying, but bending over backwards to show how you’re maybe wrong, [an integrity] that you ought to have when acting as a scientist. And this is our responsibility as scientists, certainly to other scientists, and I think to laymen.

February 6, 2021

Discontinuities in Causal AI. Classical & Quantum Detectors

Filed under: Uncategorized — rrtucci @ 11:43 am

I am happy to announce that today I added 2 new chapters to Bayesuvius (my free, open source book on Bayesian Networks). The titles of the 2 new chapters are

  1.  Difference-in-Differences (DID)
  2.  Regression Discontinuity Design (RDD)

Bayesuvius now has 50 chapters and 285 pages.

DID and RDD are two applications of Rubin’s theory of Potential Outcomes (PO). In case you don’t know what PO theory is, Bayesuvius has a chapter on PO theory too.

DID is a very old and venerable method first used in 1854 by John Snow to do causal epidemiology. In 1854, Snow published a report arguing that cholera was being transmitted in London by sewage-polluted drinking water, rather than, as many believed at the time, by air (via fetid vapors called miasmas).

RDD is a method in which a treatment is influenced by the experimenter via a confounding variable X.  X exerts no influence below a threshold value \xi, but exerts a large influence for X above \xi. This discontinuous behavior in X is reflected by a discontinuity \delta in the outcome of the treatment. By measuring \delta, we can measure the causal effect of the treatment itself. For example, the treatment might be whether or not an individual is admitted to Harvard Univ., the treatment outcome might be how much money the individual earns for the first 20 years after graduating from Harvard, and X might be his SAT scores. We assume Harvard only admits students with an SAT score higher than \xi.

Perhaps the theory of RDD can be applied to classical and quantum detectors in which a discontinuity is observed (for example, in a Geiger counter or a photodetector). Classical  detectors  are designed to detect classical  behavior and quantum detectors are designed to detect  quantum behaviors. Quantum detectors are particularly sensitive because a quantum wave-function is so easily corrupted by external influences . A quantum detector might be able to detect quantum events (like an electron jumping from one energy level of an atom to another) that a classical detector might fail to detect.

A classic classical discontinuity:


“Leaping the Chasm” (1886) by Ashley Bennett, son of photographer Henry Hamilton Bennett, jumping to “Stand Rock”. See http://www.wisconsinhistory.org

January 27, 2021

New chapter on (in) Rubin’s Theory of Potential Outcomes (heavy duty causality theory stuff)

Filed under: Uncategorized — rrtucci @ 1:49 am

I am happy to announce that today I added 3 new chapters to Bayesuvius (my free, open source book on Bayesian Networks). The titles of the 3 new chapters are

  1. Potential Outcomes
  2. Instrumental Variables
  3. Instrumental  Inequality and Beyond 

 The chapter on Potential Outcomes (PO) theory is based on the excellent book “Causal Inference: the mixtape“, by Stephen Cunningham. The PO chapter is by far the longest of the 3, and I  found it quite difficult to write. A man of my limited intelligence should not be attempting such difficult and perilous mental feats. He could hurt himself! My presentation of PO theory is unusual in that I use copiously something that I call the imagine operator. The imagine operator has been immortalized (in my house at least) by a robot poet in this soon to become famous mini poem.


Judea Pearl (left) and Donald Rubin (right). The 2  fathers of PO. (Photo taken in 2014 and pilfered by me from “The Book of Why”, by Judea Pearl.)

January 17, 2021

“Causal Inference: the mixtape”, book by Scott Cunningham

Filed under: Uncategorized — rrtucci @ 1:10 am

I am currently trying to write a chapter on Rubin’s theory of Potential Outcomes (PO) for my free open source book Bayesuvius. I am learning PO theory from the following book, which I like very much:

“Causal Inference: the mixtape”, by Scott Cunningham.

Check out Scott’s book to see if you like it as much as I do. It’s available online free of charge. It will also be available in paper form starting on Jan 26, 2021.

I find Scott’s book to be clear, down-to-earth and easy to read.

I like its choice of topics. It combines Rubin’s PO theory, Pearl’s Causal DAGs, and several other methods for distinguishing causality from correlation. (Rubin was an obstinate statistician that co-invented PO theory, but foolishly refused to use Pearl’s causal DAGs to discuss PO. DAGs make PO immensely clearer and more powerful.)

The book is a textbook for a college-level course rather than a pop sci book. It includes many numeric examples plus R and Stata code, but it also does not short change the reader as far as equations and theory are concerned. The book is long (584 pages long in paper book form),  but self contained and well structured, so that you can easily locate and read only the parts that you need at the present time.

The author Scott Cunningham is a professor of economics at Baylor College, a private Baptist university in Waco, Texas. Economists have often been criticized by their own clan as being practitioners of a sourpuss dismal science. And also for no 2 economists ever agreeing about anything, except linear regression, which they unanimously believe can cure anything. This book might make you see them in a more favorable light, as it has done for me.


Scott Cunningham,  working on a cure for baldness that uses linear regression and wine.

January 14, 2021

“Element AI” flameout portends Mass Extinction of Quantum Startups

Filed under: Uncategorized — rrtucci @ 11:35 pm

According to Wikipedia and Crunchbase, the startup Element AI was founded just 4 years ago (Oct 2016). During that time, it received a total of $257M financing from VC firms and from the Canadian government. At its height, it employed about 500 people. One of its cofounders was U. Montreal professor and Turing Award winner, Yoshua Bengio . Element AI representatives appeared in numerous photo-ops with Canadian Prime Minister Justin Trudeau. It seemed nothing could go wrong; they were given carte blanche. But today I learned from an article in the Globe and Mail that ElementAI is being sold as scrap metal to a Silicon Valley company (ServiceNow) for less than $200M.  

Several of the “red flag” traits (see list below) of Element AI are also shared by many quantum startups. This doesn’t augur well for those quantum startups that share 4 or more of these traits, does it? 

  • software only, no hardware
  • selling pricey software that very few people want to pay for because the open source community and monopolies such as Google already provide comparable free open source software.
  • revenue mostly from consulting,
  • few clients
  • crowded field
  • no net profit 4 years after it was founded
  • excessive amounts of VC funding
  • University Professor as cofounder

Actually, the situation with quantum startups is much more bleak than with AI startups. AI algorithms already produce amazing, profitable results, whereas quantum computing won’t produce a profit until the distant goal of fault-tolerant quantum error correction is achieved. Right now we are in the so called NISQ quantum disadvantage Era, the Quantum Ponzi Era, the Quantum Winter.


Element AI Team photo. Some say this Canadian branch of the human species  (homo Trudeau-ensis AI inhabilis) is now extinct. Also, homo Trudeau-ensis quantum inhabilis is in the endangered list.


Indentifiability Discussion on Twitter

Filed under: Uncategorized — rrtucci @ 11:35 pm

Check out this interesting discussion on Twitter about identifiability border cases in Pearl Causality.  See, for example, my free open source book Bayesuvius  for an introduction to Pearl Causality. In Pearl Causality, the do-conditional P(y|do(\underline{x})=x) is said to be identifiable if it can be expressed in term of the probability distribution P(y,x,t), where x,y, t are the only observed variables. One example where this do-conditional is identifiable is when the  back door (BD) criterion is met. The BD criterion is a purely topological constraint (i.e., it depends solely on the structure of a DAG). If the BD criterion is met, then one can prove that this do-conditional can be evaluated via the following adjustment formula:

P(y|do(\underline{x})=x)=\sum_t P(t) P(y|x, t)

P(y|x,t) inside the sum on the right hand side is undefined when P(x,t)=0. If that happens, then the do-conditional can no longer be evaluated by this adjustment formula. There is still the possibility that it could be evaluated using a different adjustment formula. If  no well defined adjustment formula exists, then the do-conditional is not identifiable.

Twitter is a very unlikely and inefficient place to have a discussion about this topic, because Twitter does not support LaTex and its interface for presenting conversations is, in my opinion,  quite messy and might lead you to miss some comments. Nevertheless, an interesting discussion about this has broken out around Judea Pearl’s Twitter account @yudapearl. I encourage others to listen and contribute if possible to the discussion. Even a dummy like me has tried to contribute. Here are my 2 cents worth of contribution

Quantum Ponzi Scheme. How it works.

Filed under: Uncategorized — rrtucci @ 11:35 pm

Proof of d-separation theorem

Filed under: Uncategorized — rrtucci @ 11:35 pm

My book Bayesuvius does not yet have a proof of the d-separation theorem (i.e., That d-separation implies conditional independence.). I would like to include a proof of this theorem in Bayesuvius in the future. An interesting thread has arisen recently around Judea Pearl’s twitter account @yudapearl with links to websites where such a proof can be found. The purpose of this blog post is to store a link to that thread in a place where I can find it in the future.




December 25, 2020

Bayesian Networks, Haiku-ish poetry

Filed under: Uncategorized — rrtucci @ 8:29 am

I, Robot

Let other robots talk(.),

while I

talk(.), do(.) and imagine(.)


This poem is dedicated to Judea Pearl and his work. The title “I,Robot” has a long and fascinating history.

See also history of title “I, Claudius”.

Seth Lloyd, the Jeffrey Epstein enabler, will be allowed to continue teaching at MIT with slightly reduced workload and pay

Filed under: Uncategorized — rrtucci @ 1:11 am


Seth Lloyd’s twin brother


Seth Lloyd’s twin brother

I’ve reported before how on Jan 2020, Seth Lloyd was suspended from his job as MIT professor, because he accepted a bribe of about $300K to promote the pedophile and owner of a child prostitution ring, Jeffrey Epstein.

Today, I learned that Lloyd will be allowed to continue teaching at MIT with slightly reduced workload and pay. What a disgusting disregard of students’ wishes and safety, and of Ethics and Justice. penalty=more paid vacation days, is a ridiculous penalty for a serious breach of ethics. They probably also considered taking his iPhone away for a week, but that penalty was broadly defeated because it was considered too harsh.

This pardon was granted only a few days ago, during final exam week at MIT, right before the Christmas break. So I’m sure it will engender future related news which I will report on as they develop.

MIT students have previously held a sit-in to protest Lloyd being allowed to teach. In this era of Covid-19 and increased online teaching, sit-ins are not going to be very easy, wise or effective. I would not be surprised if the next acts of protest rely more on the Internet. Cyber-resistance could range from legal to illegal acts, and need not be centrally organized. Legal acts could include boycotting products associated with MIT corporation members, and collecting protest signatures of the parents of MIT students. Illegal ones could include attacking personal computers of MIT managers, MIT professors and MIT corporation members. Attacking the websites of MIT/MIT-Mech Eng. Dept/Seth Lloyd’s course. etc. Attacking the websites of corporations associated with MIT corporation members.

Problem Set 1: Compile an open source database of major MIT donors and of corporations in which MIT corporation members are members of the board.

December 23, 2020

Matthias Troyer: “GPUs will run circles around QCs for a long, long time.” (approx. quote)

Filed under: Uncategorized — rrtucci @ 11:07 pm

During an online conference (Q2B-2020), Matthias Troyer (Microsoft apparatchik)  made the following points. 

  • qc’s will never be useful for big data problems due to memory and  bandwidth limitations.
  • Grover type quadratic speedups are worthless due to the extra overhead of fault-tolerant quantum error correction.
  • QRAM (quantum random access memory) and fault-tolerant quantum error correction, which are assumed by many quantum computing algorithms, are distant pipe dreams which are nowhere in sight.
  • GPUs will run circles around qc’s for a long, long time.

Troyer slide at Q2B-2020: (I don’t know how he got these numbers, but I believe them. Although Matthias can be quite political, and not exceptionally ethical (a long story behind that), he is quite competent in qc.)


December 18, 2020

Fucked Quantum Company

Filed under: Uncategorized — rrtucci @ 8:14 pm

Fucked Company was a legendary website that operated in the years 2000-2007, during the dot com bubble years (1995-2005). It allowed current and former employees to post anonymous reviews of their companies, much like Glassdoor does today, but much more critical. It was sued many times, and legal costs eventually drove it out of business. In 2007, it withdrew all its content, and replaced it by a home page with a simple message:

Fuckedcompany is… fucked.
R.I.P. 2000-2007. If you’re just now seeing this website for the first time, ask someone who was in the internet business during “round 1” to tell you all about it.

Nowadays, its URL has been taken over by a porn site.

I believe most quantum computing startups today are fucked companies, so I decided to start my own version of Fucked Company, but for quantum only. 13 years after Fucked Company closed its doors, the technology available to me is much more advanced and easier to use for this task. Twitter, WordPress and Glassdoor, used in combination, have yielded a perfect tool to address this job. I want to credit our loser ex-U.S.-president for giving me the idea of using Twitter, and for making Twitter so popular. So, what I’ve been doing is re-posting Tweets, the same battery of tweets, 3 times a day (My daily Twitter Trifecta). Each tweet criticizes a specific company in non-sue-able parody style. And it costs me nothing, which is important, because I am as poor as a church mouse. So far, I haven’t run into trouble with the Twitter authorities. Thanks, Jack Dorsey!!  (although your company and that beard are fucked too!) Check out my twitter account: https://twitter.com/artistexyz @artistexyz

Technical: So far, I am posting tweets by hand. I may try to automate this (as a cron job?) later on.

Philosophical: Do I think this will change anything? I harbor no such illusions. But it sure is fun giving an ulcer to dishonest, self-centered people.

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