I'm from Mexico City, where I work as a Data Scientist, I have a BSc in Applied Mathematics, and I've been wondering what can I do to help the looming climate crisis. I stumbled into this forum a couple of months ago, and I've been lurking ever since.

I would love to pick all of your brains about things like:

- What's a good field to get into to hopefully make some impact in this regard? Is a MSc in Applied Math a good starting point?
- Is there a place in the private industry for this kind of work? Do you know of any startup/enterprise that is somehow aiming to "save the world"?
- Would love to get involved in one of the study groups. Which do you recommend?

Not very technical or mathematical questions, but a starting point for me at least. Would love to get involved and get to know you all!

]]>Hasselmann did much early work on nonlinear wave modeling and established a method for discriminating natural climate variation from the AGW trend.

https://www.nobelprize.org/prizes/physics/2021/press-release/

]]>I'm Éricles, a brazilian (almost graduated) student of applied mathematics, who's just interested in understending the Universe from the fundaments. As Bruce Lee said, every kind of knowledge is ultimately self knowledge - so in the end what I'm into is getting to know myself better.

I'm also interested in backpacking and, as of late, vegan cooking, laying the path for general natural intelligence and attaining enlightenment.

]]>Am interested in Category Theory application to classification of Airborne Wind Energy Systems (AWES), which is a Work Package in process by the National Renewable Energy Lab (NREL) for the International Energy Agency (IEA). There are many ways to define computable knowledge-based engineering ontologies, and many researchers have specific skills, but Categorical Diagrams are especially intuitive, powerful, and rigorous for knowledge representation teamwork.

With regard to Green Mathematics and Azimuth's Values Commitments, AWE, also known as "Kite Energy", has tremendous potential to perhaps resolve the Holocene Extinction (or make it worse) because no other renewable energy source is so vast, dense, and ubiquitous as Upper Wind. The futurisms are mind-blowing, from game-changing green-energy super-abundance, to decisive climate geo-engineering, to levitating civilization en-masse for a techno-utopian Golden Age (Aerotecture).

Its a mathematical engineering-physics wonderland to contemplate "polymerizing the sky" by directly embodied metamaterial topologies at extreme-scale, with analog-QM phonon dynamics, sonic relativity, and so on. These dynamics apply to any geophysical flow; wind, water, solar wind, etc.. Precise AWES Categorization may inform a Multi-Physics Multi-Solver Sim, to run on an exaflop supercomputer NREL will have access to in 2022.

A starting puzzle, a Rabbit Hole Entrance into exotic AWE science-

A large ship tows another by a polymer rope (hawser) a few cm in diameter. The towed ship's drag and velocity amount to 10MW of thermodynamic work, yet the polymer rope conveying 10MW remains cool to the touch(!) Explain this mechanical superconducting (conservation of energy) according to Phonon QFT or thermodynamics. Extra points for a Feynman or Categorical Diagram.

"We might extend the application of [wind] power to the heights of the clouds, by means of kites."

John Etzler, 1833

]]>I am a Brazilian computer science student almost finishing my undergrad degree. Last year I stumbled upon the wonderful world of functional programming languages and type theories and haven't stopped exploring since. Even one year of constant study later I still feel like I've just started learning, and that is a wonderful thing!

I've started officially studying algebra and topology as a special student for a master's degree in mathematics. I want to study category theory as it can be used to give semantics to type theories and is very elegant. I like exploring mathematical foundations and, currently, my favorite is the Elementary Theory of the Category of Sets (ETCS; which should be called the Elementary Theory of the Category of *Types*).

I am truly excited to be here.

]]>I am an undergraduate student of mechanical engineering in India. Through my maths teacher, I was introduced to category theory, algebra and functional programming. I am only now beginning to wade into this world but I am captivated by what I see. I hope to learn lots and understand these subjects deeply.

Presently, I am working my way through Paolo Aluffi's Algebra : Chapter 0, and MIT's Programming with Categories course. To teach myself Haskell, which also happens to be my first real exposure to programming, I am using Julie Moronuki's and Christoph Allen's Haskell Programming From First Principles.

Certainly I wish to interact with the persons on this forum! I would like to use what I learn to help other people in any way I can one day, perhaps through teaching, writing and by doing mathematics itself.

I am happy to meet you all!

]]>it is really exciting to be on this Forum and I hope to share a lot of ideas, work or even just suggestions with you.

I am a first year PhD student in Mathematics at Rome (Tor Vergata), working in Operator Algebras and Category Theory and their applications in Mathematical Physics, my main interest is the concept of Entropy and I am working on it in two projects: the first one is in AQFT on curved spacetimes and the other is in categorification of noncommutative probability and the notion of entropy therein.

I arrived here thanks to the work of John Baez: in it I saw beautiful applications of the abstract study of symmetries in other fields, not just plain abstract/esthetical applications but rather also actual applications which shed light upon the 'mathematisation' of concepts in different areas.

My personal approach with trying to think a little bit outside the box, which is something that I would like to deepen here, began with the study of the Kleinian approach to geometry (https://ncatlab.org/nlab/show/Erlangen+program) which I find essentially multi-disciplinary and a possible mathematical-context creator tool when analyzing or modeling mathematically unknown phenomena.

Some times ago, I found a similar approach in the book by N. N. Čencov "Statistical Decision Rules and Optimal Inference" and the field of Information Geometry provides other intuitions. Also in QFT there are "informationally-based" approach to derive the spacetime geometry from information theoretic quantities.

This might be possible also for complex phenomena, with an underlying internal geometry emerging from their information content: this is really what I want to focus on in this forum.

So let me know what do you think and if you have hints, references, etc...

]]>I am a freelance software engineer in Malaysia. The time I first heard Category Theory was when I was in a discussion with a fellow software engineer when we discussed functional programming. Then I was told about this web page adit.io/posts/2013-04-17-functors,_applicatives,_and_monads_in_pictures.html and later found Option type in Rust is actually an implementation to this.

I then try to learn Category theory but couldn't find one that suits my current level of understanding, they are either overly leaned towards software engineering side which put the emphasis on software engineer terms (applying them in a language I am not familiar with is another problem), or there are simply too much abstract mathematics theories involved.

Then I came across this series of talk/seminar/workshop

https://www.youtube.com/watch?v=IBeceQHz2x8

and found the 7sketches course. I find it beginner-friendly enough and went through the whole course, but as the course progresses I get more confused @.@

After finding time to finish following the lectures posted on Youtube (with the companion text), I still find myself having problems connecting the ideas presented throughout the course. Then I found the new reincarnation of the course introduced this year, where they teach programming in Haskell while applying Category Theory to it. So far this feels like a more beginner-friendly course, can't tell if this is just because of repetition and forcing myself to immerse into the subject by the exposure to materials in Category.

Not sure what can I contribute back to the community, being a total newbie in a lot of things. I have a github account: Jeffrey04 and maintain a blog for random work notes, I guess I figure out as time progresses.

Thanks for having me.

Siang

]]>My name is Emily Pillmore, and I am a Haskell Programmer by trade, recent alumnus of the ACT Adjoint 2019 school (focus: profunctor optics w/ Bartosz), and algebraic topology enthusiast.

I am currently working towards applying to Ph.D programs for the 2021 Fall Semester, and I've been very active in the NYC category theory community hosting/attending meetups both independently and through CUNY's Graduate Category Theory Seminar. We are reading Lambek's Introduction To Higher Categorical Logic, so hit me up if you're interested!

My categorical interests are mainly focused on topics in Homotopy Theory (HoTT, Homotopical Algebra, etc) and Topos theory, but I spend alot of my time in Computer Science land, so models of the lambda calculus, parametricity, and other FP-related concepts are constantly in view. I'm currently working on understanding fibrational models for System F and proof-relevant parametricity. You can approach me with any Haskell/optics questions you might have. I'd be happy to answer :)

As part of the ACT Adjoint 2019 school, we were able to produce the following:

- https://golem.ph.utexas.edu/category/2020/01/profunctor_optics_the_categori.html
- https://arxiv.org/pdf/2001.07488.pdf

Cheers, and I hope to learn lots with you all!

Emily

]]>I'm finishing a masters in computer science with a thesis in few-shot learning. I'm glad Bartosz, David and Brendan joined to make this possible, It's a great follow up on the first course by Bartosz (which I took).

My main interests are machine learning, philosophy of science and philosophy of mathematics. I found in category theory a sufficiently expressive language to make map common practices in different scientific fields, such as abstraction, inference, modeling, experimentation, imaging, etc. Hope to take this research interest forward in the future. Brendan Fong PhD thesis is fascinating!

Greetings from Mexico City.

]]>Though I am still at a very nascent stage in category theory but lots of Scala data type are now making sense.

Hopefully, by the end of the MIT course, I would be able to gather more knowledge with the help of discussion on this forum

]]>I'm also the administrator for the forum.

It's great that people from the Programming with Categories course will be chatting here. Let me know if there is anything I can do to help. I have created a new category for this course.

Here's a blog I am creating.

]]>Though I have used terms from financial accounting and economics, I do not think the costs and benefits of our actions can be reduced to monetary values. For example, I think Gross National Product is often a poor measure of the well-being of a nation. It can be just an indication of corpulence and waste.

As an engineer, I am inclined to convert most costs to energy input, regardless of whether this energy comes from renewable sources. Expending more energy generally means having bigger impacts on the environment, and with great energy expenditure comes great responsibility. Even if we were to find a way of making electricity without a significant environmental impact, the use of this magic resource would inevitably have an impact.

Some of this energy-equivalent accounting can be awkward. The manufacture of electric vehicles consumes mineral resources such as Cobalt for their batteries. We need some way to set this cost against the costs of burning fuel in internal combustion engines, before we say that EVs are so much better than ICEs. An interesting point here the true cost of mining Cobalt ore. Currently, a significant amount of this mining is ultimately done by poor people, including children, using their bare hands and only the crudest tools. This does not cost as much as mechanised mining in terms of direct energy inputs such as fuel, but must surely have a cost in other terms.

]]>My name is Glyn Adgie. I am an electronics design engineer by training and job title, but I frequently deal with other fields of engineering in the course of my work. I have investigated the causes and cures of corrosion, and contributed to the redesign of a product that suffered premature failures due to metal fatigue. I have some experience in software design, as many electronic products have a firmware component these days.

Outside of work, I have many interests, some of which have an ecological component. For example, I am concerned about the environmental costs of agriculture and the food supply chain as a whole. At a personal level, dietary choices and cooking methods come into this. One hopes that the right personal choices, if made by enough people, will change our agricultural and food supply methods for the better, just through economic forces.

I will now put some thought to some more specific discussion topics.

]]>I'm Ian White, and I'm trying to create a new political party based upon the principles of Jainism.

Jainism and Environmental Philosophy, Aidan Rankin's new book, seems to explain well the connection between Jainism and ecology.

I first became aware of John (Baez) by reading his 'Tale of n-Categories' about 18 years ago now, while learning Haskell.

I use the handle 'votejainism' and can be found at various locations on the internet such as twitter, github, vimeo, vk, bitchute, etc. ]]>

My main interests are Physics, Math and CS, so I'm curious of the applications of CT in these fields. However I'm also curious about how could it be used in other less theoretical fields.

]]>I started researching quite a bit then, and I found category theory which I just loved. I found out that that's the stuff I'd like to work on in the future. I'm now learning mostly from the videos of David Spivak at LambdaConf and from 'Category Theory' by Steve Awodey.

https://www.youtube.com/watch?v=IBeceQHz2x8&list=PLFTBfi-r3xj2jEpzoKl2koVLg1UrE9YL-

Since I started learning category theory (pretty recently), I have begun finding categories in really non-mathematical things, and that only made me love Category Theory even more.

I have always been fascinated by mathematics and theoretical computer science, and I'm planning to continue my career as a researcher in these fields. I have founded clubs, and discussion groups and other things like this forum to try to find like-minded people to work with them on Category Theory. And that's what made me join this forum. In fact, I'm planning to change to a double major of mathematics and computer science next year to help push myself into research and academia. In this regard, Category Theory and Homotopy Type Theory are prime candidates for future research fields I could work on because I simply loved them.

Incidentally, it turned out a main focus of this project is environmental protection, which is a thing I'm really really interested in. So that's 2 in 1 :P

I hope that I can get to know people and learn more about category theory from this forum as well as contribute to the community.

]]>I've been trying to apply category theory to a couple topics:

Building a library / example elegantly embedding anyon vector spaces in Haskell - http://www.philipzucker.com/a-touch-of-topological-computation-3-categorical-interlude/

Automatic differentiation - http://www.philipzucker.com/reverse-mode-differentiation-is-kind-of-like-a-lens-ii/

Conal Elliot's compiling to categories - http://www.philipzucker.com/compiling-to-categories-3-a-bit-cuter/

Also I've recently been tinkering with some ideas about how to do something "category"eque with convex programming. Definitely be interested if you've got any tips/ references. https://github.com/philzook58/ConvexCat

]]>I am applying Category Theory to business, specifically in the way we design software. We are using OLOGs and String Diagrams to build graphical representations directly connected to the functional requirements.

Graphics are used by Subject Matter Experts with no understanding of the underlying math or science for the system. Instead they are given a ubiquitous language (developed interactively at the domain level) with which to communicate and collaborate across specific subject areas and specialties. I am applying Conceptual Spaces, Topology, and the ideas from Gardenfors (along with Brouwer, Heyting, and Goldblatt) to bridge the Language semantics of graphics, business processes, and software development. Most of our software is used for internal process communication and Category Theory has proven to be the proper tool for the job.

Adding guidance for how to apply that to business processing and software design is my focus. I am not referring to "functional programming" though that does play a role. I am referring more to the business process and understanding the information science behind the process outside of any applied technology.

]]>I tried reading Conceptual Mathematics: A First Introduction to Categories by Lawvere and Schaunel about a year ago and, while I found the "flight of a bird as a map from time to space" diagram to be very charming, I was ultimately unable to really understand the text. I'm hopeful that this course and forum will be able to guide me (and others!) through Seven Sketches.

I live and work in Brooklyn, where I spend as much of my time as possible seeing live music and drinking with friends. I studied architecture (as in buildings, not software) in undergrad, and it is probably the subject I enjoy talking about the most. If you have an interest, let's talk bricks!

My only other active side project is a visual demo of sorts for the Raft consensus algorithm using a few raspberry pis and some LED matrices to represent state. I just finished up the LED control code in Python and am moving on to Raft itself now. I'm on the fence for language choice, but may give Elixir a go.

Thank you for hosting the course John! Excited to give category theory another crack.

]]>The quantitative version of Boole's logic of subsets is just finite logical probability theory as developed by Boole in his *Laws of Thought*. Rota always held that probability (i.e., the normalized size of a subset) is to subsets as information is to partitions.

$$\frac{\text{Probability}}{\text{Subsets}}=\frac{\text{Information}}{\text{Partitions}}$$

The key to working that out was to see the analogy between an "element of a subset" and a "distinction of a partition," where a *distinction* or *dit* of a partition is an ordered pair of elements of the underlying set \(X\) that are in different blocks or parts of the partition. The *indistinctions* or *indits* of a partition are the ordered pairs of elements in the same block or part of the partition. Hence the set of all indits of a partition is just the binary equivalence relation associated with the partition, and the set of all dits of a partition, the *ditset* \(dit(P)\), is the complementary binary relation called an *apartness relation* or just a *partition relation*. The *logical entropy* \(h(P)\) of a partition is just the normalized size of the ditset:

$$h(P)=\frac{|dit(P)|}{|X^2|}.$$

Logical entropy is related in a definite way to Shannon entropy. All the Shannon definitions of simple, joint, conditional, and mutual entropy can be obtained by a uniform requantifying transformation from the corresponding definitions in logical information theory. Moreover, logical entropy (unlike Shannon entropy) is a measure in the sense of measure theory, and thus the logical definitions of simple, joint, conditional, and mutual logical entropy of partitions is just the measure applied respectively to the ditsets, the union of ditsets, the difference of ditsets, and the intersection of ditsets. Indeed, logical entropy is a probability measure with the interpretation that \(h(P)\) is the probability of getting a distinction in two independent draws from the set \(X\). The basic paper developing logical information theory (and spelling out the comparisons with the closely related Shannon theory) was also published in the Logic Journal of the IGPL.

I went into a little detail about logical information theory as the quantitative version of partition logic since it bears on the question of which of the opposite partial orderings, the coarseness ordering or the refinement ordering, should be used on partitions. Since refinement increases the number of distinctions, it increases logical (and Shannon) entropy so the refinement ordering seems best if one is emphasizing the ordering of partitions according to their information content measured by logical or Shannon entropy.

Another topic of my research has been "heteromorphisms" which are morphisms between the objects of different categories, e.g., the canonical injection of the set of generators into the free group on that set. Homomorphisms may be treated formally by hom-functors, and heteromorphisms are treated formally by the "het-functors" or *profunctors* that appear later in the course. For one reason or another, Mac Lane and Eilenberg did not include heteromorphisms in their basic "ontology" for category theory even though they are just as much a tool for the proverbial "working mathematician" (referenced in the title of Mac Lane's text) as are homomorphisms. The French school of category theory, e.g., the Grothendieck school, is much less prudish and let hets 'out of the closet' as just "morphisms" routinely. The differing attitude about hets comes out in the treatment of adjoint functors. The simpler and I think more natural treatment of adjoints was developed by Bodo Pareigis in the late 60's and published in his text translated into English as: Pareigis, Bodo. 1970. *Categories and Functors*. New York: Academic Press. It also comes out in what one takes as more important or more basic: adjoint functors or representable functors. Grothendieck gives representable functors the pride of place, whereas the American school puts the emphasis on adjoint functors. Hets, representable functors, and adjoints are all tied together in the Pareigis treatment of adjoints. Take the het-functor whose value \(\text{het}(X,G)\) is the set of set-to-group maps from a set \(X\) to a group \(G\). The underlying set functor is just the right-representation of those hets by homs in the category of sets, and the free-group functor is just the left-representation of those *same hets* by homs in the category of groups. Thus one has the natural isomorphisms:

$$ \text{hom}(F(X),G)\cong \text{het}(X,G)\cong \text{hom}(X,U(G)).$$

The heterophobic American school always leaves out the middle term of hets and just defines an adjunction using the natural isomorphism between the hom-sets. All left- and right-representations of a het-functor define a pair of adjoint functors, and given a pair of adjoint functors, there is a het-functor so that the given adjoints are isomorphic to the left- and right-representations of the het-functor. All this holds as well for adjunctions on preorders or Galois connections. An introductory paper is here.

]]>