Other Alef’s corner posts

]]>Other Alef’s corner posts

]]>To cheer you up in difficult times here are songs by Sabine Hossenfelder and by Tom Lehrer. I like the music and lyrics and the unusual combination of science, humor and satire.

Sabine Hossenfelder : Outer space*

Tom Lehrer: That’s mathematics

Sabine Hossenfelder: Theories of everything

Tom Lehrer: Lobachevsky

Sabine Hossenfelder: Schrödinger Cat (The song follows by a physics explanation).

Tom Lehrer: The Professor’s Song (2:55 there is delta for every epsilon)

Sabine Hossenfelder: Ave Maria

Tom Lehrer: The Vatican Rag

Sabine Hossenfelder: Ivory Tower

Tom Lehrer: Elements

Sabine Hossenfelder: Not a Toy

Tom Lehrer The Hunting Song

Sabine Hossenfelder: A Million Miles

Tom Lehrer: Pollution

Sabine Hossenfelder: This is how I pray

Tom Lehrer: Wernher von Braun

Sabine Hossenfelder: Galaxy Song, Monty Python (cover)

Tom Lehrer: Poisoning Pigeons In The Park

Sabine: Catching light

Tom: National brotherhood week

On GLL: Sabine Hossenfelder is featured in this post, and is also mentioned here; Tom Lehrer is featured in this post and this one and is also mentioned here.

Playlists: Tom Lehrer; Sabine Hossenfelder.

Sabine Hossenfelder (left) Tom Lehrer (right)

*”Outer space” is a famous mathematical concept as well.

]]>Every day since March 27, 2020 Noam Elkies (Noam’s home page) uploaded a new piece of piano improvisation. The Hebrew title of his page is “Music will let you forget the plague”.

Here is the very first comforting piece a la Schumann/Chopin; a piece based on the* the Marseillaise; Bim Bam Bom (a popular Israeli song), and a tango. And yesterday, Yesterday!
*

And excerpt from a forthcoming book on Chess and Mathematics by Noam Elkies and Richard Stanley: 12 page PDF file. A paper by Noam Elkies and Richard Stanley: The mathematical knight: PDF document.

See also these three posts on GLL (I, II, III).

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A comparison between the Google estimator U for the fidelity and two improved estimators that we studied MLE (maximum likelihood estimator) and V (a variant of U). (More figures at the end of the post.)

Here are some links on quantum matters. I hope to return to them in more detail in some future posts.

Yosef Rinott, Tomer Shoham and Gil Kalai: Statistical aspects of the quantum supremacy demonstration, (arXive)

**Abstract:**

The notable claim of quantum supremacy presented by Google’s team in 2019 consists of demonstrating the ability of a quantum circuit to generate, albeit with considerable noise, bitstrings from a distribution that is considered hard to simulate on classical computers. Verifying that the generated data is indeed from the claimed distribution and assessing the circuit’s noise level and its fidelity is a purely statistical undertaking.

The objective of this paper is to explain the relations between quantum computing and some of the statistical aspects involved in demonstrating quantum supremacy in terms that are accessible to statisticians, computer scientists, and mathematicians.

Starting with the statistical analysis in Google’s demonstration, which we explain, we study various estimators of the fidelity, and different approaches to testing the distributions generated by the quantum computer. We propose different noise models, and discuss their implications. A preliminary study of the Google data, focusing mostly on circuits of 12 and 14 qubits is discussed throughout the paper.

I am greatly enjoying working with Yosi and Tomer, and I hope to devote a special post to the very interesting statistics of the Google supremacy experiment.

Here is how the paper concludes

Over the past four decades, the very idea of quantum computation has led to many advances in several areas of physics, engineering, computer science, and mathematics. I expect that the most important application will eventually be the understanding of the impossibility of quantum error-correction and quantum computation. Overall, the debate over quantum computing is a fascinating one, and I can see a clear silver lining: major advances in human ability to simulate quantum physics and quantum chemistry are expected to emerge if quantum computational supremacy can be demonstrated and quantum computers can be built, but also if quantum computational supremacy cannot be demonstrated and quantum computers cannot be built.

Some of the insights and methods characteristic of the area of quantum computation might be useful for classical computation of realistic quantum systems – which is, apparently, what nature does.

The link above is the most recent version that will be updated; Here is the arXive version. A discussion on Hacker News.

My Dec 19 2019 (B.C.) surprise lecture at the mathematics of quantum computing school and the afternoon panel on the same day. It turned out that the lecture was videotaped. The slides can be seen in this post. Remarkably, social distancing was pioneered by the session chair toward the end of the lecture (while not justified in that case).

Here once again again is the link for the panel discussion on quantum supremacy of the same day (reviewed here) . Here is a quote of mine from the panel.

Of course, it is important to think what are the implications of quantum supremacy, is it useful? what does it say on the extended Church-Turing thesis? on prospects for quantum error-correction and universal quantum computers? etc. but I think that in the next few years one thing that we need to also concentrate on is the following question: Is the Google experiment correct? Is this a correct scientific verification of quantum supremacy?

Four slides from my USTLC zoom lecture. (Click to enlarge.)

Here is the videotaped Zoom presentation and here are the slides.

Poems by Peter Shor and Renan Gross (click to enlarge)

Peter Shor pioneered quantum poetry for the skeptics over Twitter. There were many very nice contributions all over social media by Renan Gross, John Dowling, Vidit Nanda, ⟨dl|yonge|mallo⟩, Alfred Marcel Bruckstein, Kenneth Regan, and others. **Keep the quantum poems coming!** Of course, the poems should be taken with humor. Here is a small taste.

Understanding nature and ourselves is a worthy dream

Requiring no interaction with the supreme

A quantum computer from Google,

Turned the Church-Turing thesis to strudel.

And yet there remain,

Many doubting this claim,

And we lash all of them with wet noodles.

“There once was a quantum computer

Whose pet was a five-legged hamster …”

So Peter and Gil

Their grandchildren will

Tell “…happy they lived ever after”

Avi suggests a kids’ chorus saying “yeah, right” or “sure, sure”, after each line

For sale: quantum computer. Never used.

Michelson and Morley weren’temployees.

Various estimators for the fidelity for the Google data compared to simulations.

The model expected values compared to the empirical distribution. On the left for the real data and on the right for simulated data. As it turned out the Google noise model does not fit for the sample data. (Our readout model provides only a small improvement.)

The size biased distribution fits the model very well.

]]>Rota’s Basis Conjecture holds asymptotically, by Alexey Pokrovskiy

**Abstract:** Rota’s Basis Conjecture is a well known problem from matroid theory, that states that for any collection of n bases in a rank n matroid, it is possible to decompose all the elements into n disjoint rainbow bases. Here an asymptotic version of this is proved. We show that it is possible to find *n − o(n)* disjoint rainbow independent sets of size *n − o(n)*.

A **rainbow **basis is a basis with one element from each collection.

(I thank Nati Linial for telling me about it.)

Another way to formulate Rota’s basis conjecture (for representable matroids) is that if *B*_{1}, *B*_{2}, …, *B _{n}* are

1. the *n* vectors in row *i* are the members of the *i*th basis *B _{i}* (in some order), and

2. in each column of the matrix, the *n* vectors in that column form a basis of *V*.

If all the bases are the standard basis then this reduces to the existence of Latin squares.

**Unrelated trivia question:** AGC-GTC-TGC-GTC-TGC-GAC-GATC-? what comes next in the sequence?

We mentioned Rota’s basis conjecture in various earlier posts. A classic paper on the subject is the 1989 paper by Rosa Huang and Gian Carlo-Rota. Three and a half years ago Timothy Chow lunched a polymath project (Polymath 12) to solve it. (Here is my post on the project with various variants of the conjecture, the first post on the polymath blog, and the wiki). See this post for several famous conjectures by Rota, and this post about the related Alon-Tarsi conjecture.

]]>Consider a unit vector That is . Consider all () signed sums where each is either 1 or -1.

**Theorem (Keller and Klein (2020) asked by Boguslav Tomaszewski (1986)): **For at least signed sums

Another way to state the theorem is that the probability of a signed sum to be in the interval [-1, 1] is at least 1/2.

To see that this is best possible consider the case that and let be non zero. For the sum in question to exceed one we need both summands to have the same sign which happens half of the times. There is another example of importance, the vector . Here 3/8 of the absolute values of signed sums (6 out of 16) are below 1 (in fact, equal to zero), 1/2 equal to 1 and 1/8 exceed 1. Holzman and Kleitman proved in 1992 that the fraction of absolute values of signed sums below 1 is always at least 3/8.

Congratulations to Nathan and Ohad. I will say a little more about the problem below but before that, a few more things.

Luca Trevisan posted on his blog In Theory a post “Silver linings” about two cheerful pieces of news. The first one is “Karlin, Klein, and Oveis Gharan have just posted a paper in which, at long last, they improve over the 1.5 approximation ratio for metric TSP which was achieved, in 1974, by Christofides.”

The second one is about breaking the logarithmic barrier for Roth’s theorem that we wrote about here. This was also discussed by Bill Gasarch on Computational Complexity. In the comment section of my post there is an interesting discussion regarding timetable for future achievements and how surprising they would be.

The third is about Ron Graham, a friend and a mathematical giant who passed away a few days ago. Here is a moving post by Fan Chung, a web page for Ron set by Fan, and a blog post by Dick and Ken on GLL.

The fourth is that there is a nice collection of open problems on Boolean functions that is cited in the paper of Nathan and Ohad: Y. Filmus, H. Hatami, S. Heilman, E. Mossel, R. O’Donnell, S. Sachdeva, A. Wan, and K. Wimmer, Real analysis in computer science: A collection of open problems.

The fifth is that both our (HUJI) combinatorics seminar and basic notions seminar are running and are recorded. Here are the links. (Hmm, the links are not yet available, I will update.)

Daniel Kleitman and Ron Holzman

If the s are all the same, or small, or random, then to compute the probability that the weighted sum is between -1 and 1, we can use some Gaussian approximation and then we will find ourselves in a clash of constants that goes our way. The probability will be close to a constant well above 1/2. So what we need to understand is the case where some s are large.

The problem first appeared in the American Math Monthly. Richard Guy collected several problems and challenged the readers Any Answers Anent These Analytical Enigmas? (I don’t know what the fate of the other questions is.) Holzman and Kleitman proved in 1992 that the fraction of absolute values of signed sums below 1 is always at least 3/8, and this is tight. For many years, 3/8 was the record for the original problem, until the 2017 paper by Ravi Boppana and Ron Holzman: Tomaszewski’s problem on randomly signed sums: Breaking the 3/8 barrier, where a lower bound of 0.406, was proved. The current record 0f 0.46 was proved in the paper Improved Bound for Tomaszewski’s Problem by Vojtěch Dvořák, Peter van Hintum, and Marius Tiba. The new definite result by Nathan and Ohad used some ideas of these early papers.

Let me quote what the authors kindly wrote me:

“The crux of the matter is how to deal with the case of very large coefficients (). We gave a short semi-inductive argument covering this case (this is Section 5 of the paper). The argument is only semi-inductive, as it requires the full assertion of Tomaszewski for any n'<n, and gives only the case () for . But this means that if we can handle all other cases by other methods then we will be done.

The semi-inductive argument takes only 3 pages. Handling the other cases takes 72 more pages and requires several new tools, but is closer to things that were done in previous works. (Actually, after we found the 3-page argument, we were quite sure we will be able to finalize the proof; this indeed happened, but took a year).”

Most of the paper deals with the case of small coefficients. This requires several ideas and new tools.

If all coefficients are “sufficiently small”, then we can

approximate X by a Gaussian and the inequality should follow. However, using the standard Berry-Esseen bound, this holds only if all coefficients are less than 0.16.

Nathan and Ohad showed that for Rademacher sums, namely random variables of the form , as discussed in the conjecture, a stronger Berry-Esseen

bound can be obtained, and this bound shows immediately that Tomaszewski’s assertion holds whenever all coefficients are less than 0.31. The stronger bound stems

from a method of Prawitz, presented in the 1972 paper. H. Prawitz, Limits for a distribution, if the characteristic function is given in a finite domain, which appeared in the Scandinavian Actuarial journal.

The second tool is local tail inequalities for Rademacher sums, of the form where *a,b,c,d* satisfy certain conditions. Inequalities of this kind were obtained before by Devroye and Lugosi in the 2008 paper: Local tail bounds for functions of independent random variables.

These local tail inequalities already have some other applications, e.g., to analysis of Boolean functions. They were developed and applied in an earlier paper paper of Keller and Klein: Biased halfspaces, noise sensitivity, and relative Chernoff inequalities. Let me mention my related MO question A variance tail description for continuous probability distributions.

**A stopping time argument.** Variants of Tomaszewski’s problem appeared in various fields. The problem was stated independently in a 2002 paper by Ben-Tal, Nemirovski, Roos, Robust solutions of uncertain quadratic and conic-quadratic problems. A stopping time argument introduced there (for proving a lower bound of 1/3) played a crucial role in subsequent works and the critical semi-inductive argument by Nathan and Ohad.

**Refinements of the famous Chebyshev’s inequality.** (Did you know Chebyshev’s full name? Ans: Pafnuty Lvovich Chebyshev.)

**Q1:** What can be said about families of signs that can serve as those signs for which for some vector .

**Q2:** What can be said about the complex version or even more generally about high dimensions?

**Q3:** Are there any relations to Littlewood-Offord type problems?

**Q4:** Is there any relation to the Komlos Conjecture?

See also this MO question by Luca Trevisan and this one by George Lowther.

We can ask about simpler or just different proofs for almost every result we discuss here. But here the statement is so simple…

Before we get to the post I want to mention that there are a lot of activities on the web. I may devote a special post to links and discussion (and contributing links in the comment section is very welcome.) but meanwhile a few links: 1) Advances in Boolean Function Analysis Lecture Series (thanks to Avishay Tal and Prasad Raghavendra for letting me know); 2) Online course in Foundations of Algebraic Geometry Given by Ravi Vakil from Stanford. You can take the course at varying levels of involvement. (Thanks to Tami Ziegler for telling me) A very very interesting way of online teaching. 3) A site with online mathematical lectures.

Aline Bonami with Szilard Revesz and me (2006). Aline Bonami first proved the 2-point hypercontractive inequality which is very useful in the analysis of Boolean functions. (Leonard Gross proved it independently a few years later and William Beckner found important applications to harmonic analysis.)

Our aim is to prove the hypercontractivity theorem for global functions. The proof here is taken from a joint paper with David Ellis and Guy Kindler that’ll soon be out on the Arxiv.

Here we use the notations given in the last blog post. Let us first get a feel for our hypercontractivity theorem by proving the case. Here the RHS is

We will prove the following slightly stronger version of Theorem 1 for the case.

**Proposition 2:**

Let Let Then

**Proof**: Let us write for Rearranging, we have

The noise operator in the case is by definition equal to where is the expectation over operator, and is the identity operator. Hence,

Now when expanding the 4-norm of the function , we obtain

where we used the fact that the expectation of is 0. When looking at the right hand side of the global hypercontractivity theorem, we see most of the above terms except for the one involving the third norm of the Laplacian. Indeed we have

Hence we see that the only term in the left hand side that doesn’t appear with a greater coefficient in the left hand side is the term and by AM-GM we have

which allows us to upper bound the only term appearing in the left hand side but not in the right hand side by corresponding terms that do appear in the right hand side.

Next we are going to prove a theorem that doesn’t seem to fit to our setting, but we’re going to fit it in by force. Let be finite sets. Let us write for the linear space of complex valued functions on . The space can be identified with the space where a pair of function is identified with the function

in

Given two operators , the operator is the unique operator sending to . We write for The operator can also be defined more explictly in terms of its values on functions. The operator can be understood more explicitly by noting that it is the composition of the operators and Now the operator is given by where

**Lemma 3:** Let be measure spaces with finite underlying sets. Let be operators satisfying

for all functions

Then

for all

Here the spaces and are equipped with the product measure, where the measure of an atom is the product of the measures of its coordiates.

**Proof:** For each let be given by As mentioned Hence by hypothesis, we have

We may now repeat the same process on each of the other coordinates to replace the s by s one by one.

The strategy of our proof is to take the theorem

which we established in the case for , and to turn it into an essentially equivalent statement about 4-norms. We will then get a tensorised statement for general , which we will be able to convert back into our hypercontractivity theorem for global functions. Our idea is to encode our function as a function satisfying

and

The benefit of working with rather than is that in one may move between 4-norms and 2-norms by appealing to the hypercontractivity theorem there, which gives

at the cost of some noise.

To define we use Fourier analysis of Abelian groups. Let us briefly recall it. For simplicity let us assume that where is a prime. Let be a th root of unity. For any we have a character given by The are an orthonormal basis of and we write , where Note that is the constant function, and so we have

which gives

Our mission will first be to convert the -norm of a function to the norm of a different function.

We define an encoding operator by setting

We have

as the are orthonormal and so are the Moreover, by the Fourier formula for Since -norms are always smaller than 4-norms on probability spaces, we’ve got the following corollary of Proposition 2.

**Lemma 4.** For all and all we have

We now reach the final little trick. We define a measure space whose underlying set is and where the measure is given by for and for We let be given by on and letting it be on This way Lemma 4 takes the form

The operator on satisfies where the latter refers to the noise operator on The characters satisfy and so we have the Fourier formula

We also have

and so

This will allow us to conclude that

We will also encounter the operator which by abusing notation we also call encodes

as the function on

Now finally we can get to the understanding of the operator The space is the disjoint union of spaces of the form

By definition of the tensor product, for is the function

**Proof:** Lemmas 3 and 4 yield:

for any We now have

The first equality follows from the formula and the fact that commutes with the encoding. The inequality used hypercontractivity on the discrete cube. The last equality follows from the fact that the operator preserves 2-norms.

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Once again Extraordinary news regarding Roth Theorem! (I thank Ryan Alweiss for telling me about it and Rahul Santhanam for telling me about Thomas and Olof’s earlier attempts.)

Suppose that is a subset of of maximum cardinality not containing an arithmetic progression of length 3. Let . Roth proved that .

A few days ago Thomas Bloom and Olof Sisask proved that for some

This is an extraordinary result!!! I will tell you a little more about it below.

I just heard yesterday the sad news that Ron Graham passed away. Ron was an extraordinary mathematician and an extraordinary person. I first met Ron in Montreal in 1978 and we met many times since then. Ron will be dearly missed.

From an abstract of a lecture by Thomas and Olof: “This is the integer analogue of a result of Bateman and Katz for the model setting of vector spaces over a finite field, and the proof follows a similar structure.”

A catchy (weaker) formulation which goes back to Erdos and Turan is:

Let be a sequence of integers so that , then the sequence contains an arithmetic progression of length three!!

Bloom and Sisask’s result implies, of course, Van der Korput’s result that the primes contain infinitely many 3-terms arithmetic progression as well as Green’s 2005 result asserting it for every dense subset of primes.

Szemeredi’s celabrated result extended Roth’s theorem to arithmetic progression of any fixed size, and Green-Tao celebrated 2008 result asserts that the primes (or a dense subsets of primes) contain arithmetic progression of any length. (The case of 3-term AP is so far much simpler for all the results mentioned below.)

A little more about the history of the problem below the fold

Let’s wrire . Roth proved that . Szemeredi and Heath-Brown improved it to for some $latex c>0$ (Szemeredi’s argument gave .) Jean Bourgain improved the bound in 1999 to and in 2008 to (up to lower order terms).

Erdös and Turan who posed the problem in 1936 described a set not containing an arithmetic progression of size . Salem and Spencer improved this bound to . Behrend’s upper bound from 1946 is of the form . A small improvement was achieved by Elkin and is discussed here. (Look also at the remarks following that post.)

In 2010 Tom Sanders was able to refine Bourgain’s argument and proved that . A few month later Tom have managed to reach the logarithmic barrier and to prove that

We reported about this outstanding achievement in this blog post and quoted from his paper: “There are two main new ingredients in the present work: the first is a way of transforming sumsets introduced by Nets Katz and Paul Koester in 2008, and the second is a result on the -invariance of convolutions due to Ernie Croot and Olof Sisask (2010).”

The exponent 6 for the loglog term was improved to 4 by Thomas Bloom and recently to 3 by Thomas Schoen in his paper: Improved bound in Roth’s theorem on arithmetic progressions. Schoen uses ingredients from Bateman and Katz’s work (see below).

A closely related problem in . It is called the cap set problem. A subset of is called a cap set if it contains no arithmetic progression of size three or, alternatively, no three vectors that sum up to 0(modulo 3). If $latex _n$ is a cap set of maximum size in we can ask how the function behaves. In 1995 Roy Meshulam proved, using Roth’s argument, that . Edell found an example of a cap set of size . Again the gap is exponential. What is the truth? Improving Meshulam’s result may be closely related to crossing the barrier for Roth’s theorem. In 2007 Tom Sanders managed to achieve it , not for the cup problem, but for a related problem over Z/4Z.

In 2011, Michael Bateman and Nets Katz improved, after many years of attempts by many, the Roth-Meshulam bound. They proved using Fourier methods that for some ! This was very exciting. See these two posts on Gowers’s blog (I,II). This raised the question if the new method allows breaking the logarithmic barrier for Roth’s theorem.

Tim Gowers proposed in 2011 polymath6 to try to break the logarithmic barrier for Roth based on the Bateman-Katz breakthrough. (Here is the wiki; and a related post by Sanders, and a document by Katz) This project did not get off the ground. We can regard the news as giving support that the polymath6 project was timely and of an appropriate level, and also as giving some support to an advantage of the conventional way of doing mathematics compared to the polymath way.

Next and quite recently came a startling development – the Croot-Lev-Pach-Ellenberg-Gijswijt capset bound . (Croot, Lev, and Pach gave an exponential improvement for the Z/4Z case (see this post) and a few weeks later Ellenberg and Gijswijt used the method for the Z/3Z case (see this post).)

A natural question that many people asked was how this development relates to improving the bounds for Roth perhaps even towards the Behrend bound. We discussed it a little over here and in other places. This is still an interesting possibility.

However, just a ~~few months~~ few years after the Bateman-Katz result have become obsolete for the cap-set problem, the Bateman-Katz method prevailed in this wonderful breakthrough of Bloom and Sisask giving for .

In an old post we asked: “How does behave? Since we do not really know, will it help talking about it? Can we somehow look beyond the horizon and try to guess what the truth is? (I still don’t know if softly discussing this or other mathematical problems is a fruitful idea, but it can be enjoyable.)” We even had a poll collecting people’s predictions about . Somewhat surprisingly 18.18% of answerers predicted that behaves like for some .

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Here is a web-page by a student in my “Game Theory” course where you can play several two-players variants of John Conway’s game-of-life. (A couple of variants were considered before. See, e.g. this paper.)

I really enjoyed playing Rani’s games and it can certainly cheer you up in difficult times. Questions about the game, remarks, and suggestions for improvements and for new features, are most welcome.

Maya Bar-Hillel (left) and Ester Samuel-Cahn

Here is an interesting 2006 power point presentation entitled ** How to detect lies with statistics** by Maya Bar-Hillel. This was a talk given by Maya at the conference honoring Prof. Ester Samuel- Cahn , Jerusalem, December 18-20, 2006, and it described a planned research project of Maya Bar-Hillel with Yossi Rinott, David Budescu and myself. At the end we did not pursue it, mainly because each of us was involved in various other projects (but also because we were skeptical about some aspects of it.) Ester Samuel-Cahn (1933-2015) was a famous Israeli statistician. (Here is a post by Yosi Levy in Hebrew about the conference and about Ester.)

The lecture starts with “Last year, *Statistical Science* celebrated 50 years for `How to Lie with Statistics’ the book [by Durell Huff] whose title inspired this talk.”

And here are a few other quotes from Maya’s presentation

“We are not sure a general toolkit for detecting lies with statistics can be developed. Perhaps that explains why none yet exists. We have shown just a collection of anecdotes. But they can be classified and categorized. Some do seem generalizeable, at least to some extent.”

and the conclusion

A famous quip by Fred Mosteller: “It is easy to lie with statistics, but easier to lie without them.”

Likewise, we should say: “It is possible to detect (some) lies with statistics, but easier to detect them with other means”.

Peter Keevash, Alexey Pokrovskiy, Benny Sudakov, and Liana Yepremyan’s paper New bounds for Ryser’s conjecture and related problems, describes remarkable progress very old questions regarding transversals in Latin square.

I came across a very interesting paper The topological Tverberg problem beyond prime powers by Florian Frick and Pablo Soberón with new bounds and a new method for topological Tverberg theorem in the non prime-power case.

A year ago I came across this cool facebook post by Rupei Xu

OMG! Just learned that Jaeger’s conjecture is false for every t>=3. An interesting consequence of it is that a specific version of Goddyn’s conjecture on thin spanning trees is false, which shows some negative evidence that the thin spanning tree approaches may fail to lead to a constant factor approximation algorithm for ATSP!

Let me mention two problems I posted 6-7 years ago about Conway’s game of life. Conway’s game of life for random initial position and Does a noisy version of Conway’s game of life support universal computation?

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