The Cartesian Cafe

The Cartesian Cafe is the podcast where an expert guest and Timothy Nguyen map out scientific and mathematical subjects in detail. This collaborative journey with other experts will have us writing down formulas, drawing pictures, and reasoning about them together on a whiteboard. If you’ve been longing for a deeper dive into the intricacies of scientific subjects, then this is the podcast for you. Topics covered include mathematics, physics, machine learning, artificial intelligence, and computer science. Content also viewable on YouTube: and Spotify. Timothy Nguyen is a mathematician and AI researcher working in industry. Homepage:, Twitter: @IAmTimNguyen Patreon:

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Wednesday Aug 02, 2023

Boaz Barak is a professor of computer science at Harvard University, having previously been a principal researcher at Microsoft Research and a professor at Princeton University. His research interests span many areas of theoretical computer science including cryptography, computational complexity, and the foundations of machine learning. Boaz serves on the scientific advisory boards for Quanta Magazine and the Simons Institute for the Theory of Computing and he was selected for Foreign Policy magazine’s list of 100 leading global thinkers for 2014.
Cryptography is about maintaining the privacy and security of communication. In this episode, Boaz and I go through the fundamentals of cryptography from a foundational mathematical perspective. We start with some historical examples of attempts at encrypting messages and how they failed. After some guesses as to how one might mathematically define security, we arrive at the one due to Shannon. The resulting definition of perfect secrecy turns out to be too rigid, which leads us to the notion of computational secrecy that forms the foundation of modern cryptographic systems. We then show how the existence of pseudorandom generators (which remains a conjecture) ensures that such computational secrecy is achievable, assuming P does not equal NP. Having covered private key cryptography in detail, we then give a brief overview of public key cryptography. We end with a brief discussion of Bitcoin, machine learning, deepfakes, and potential doomsday scenarios.
I. Introduction
00:17 : Biography: Academia vs Industry
10:07 : Military service
12:53 : Technical overview
17:01 : Whiteboard outline
II. Warmup
24:42 : Substitution ciphers
27:33 : Viginere cipher
29:35 : Babbage and Kasiski
31:25 : Enigma and WW2
33:10 : Alan Turing
III. Private Key Cryptography: Perfect Secrecy
34:32 : Valid encryption scheme
40:14 : Kerckhoffs's Principle
42:41 : Cryptography = steelman your adversary
44:40 : Attempt #1 at perfect secrecy
49:58 : Attempt #2 at perfect secrecy
56:02 : Definition of perfect secrecy (Shannon)
1:05:56 : Enigma was not perfectly secure
1:08:51 : Analogy with differential privacy
1:11:10 : Example: One-time pad (OTP)
1:20:07 : Drawbacks of OTP and Soviet KGB misuse
1:21:43 : Important: Keys cannot be reused!
1:27:48 : Shannon's Impossibility Theorem
IV. Computational Secrecy
1:32:52 : Relax perfect secrecy to computational secrecy
1:41:04 : What computational secrecy buys (if P is not NP)
1:44:35 : Pseudorandom generators (PRGs)
1:47:03 : PRG definition
1:52:30 : PRGs and P vs NP
1:55:47: PRGs enable modifying OTP for computational secrecy
V. Public Key Cryptography
2:00:32 : Limitations of private key cryptography
2:09:25 : Overview of public key methods
2:13:28 : Post quantum cryptography
VI. Applications
2:14:39 : Bitcoin
2:18:21 : Digital signatures (authentication)
2:23:56 : Machine learning and deepfakes
2:30:31 : A conceivable doomsday scenario: P = NP
Further reading: Boaz Barak. An Intensive Introduction to Cryptography
Twitter: @iamtimnguyen

Wednesday Jun 14, 2023

Sean Carroll is a theoretical physicist and philosopher who specializes in quantum mechanics, cosmology, and the philosophy of science. He is the Homewood Professor of Natural Philosophy at Johns Hopkins University and an external professor at the Sante Fe Institute. Sean has contributed prolifically to the public understanding of science through a variety of mediums: as an author of several physics books including Something Deeply Hidden and The Biggest Ideas in the Universe, as a public speaker and debater on a wide variety of scientific and philosophical subjects, and also as a host of his podcast Mindscape which covers topics spanning science, society, philosophy, culture, and the arts.
In this episode, we take a deep dive into The Many Worlds (Everettian) Interpretation of quantum mechanics. While there are many philosophical discussions of the Many Worlds Interpretation available, ours marries philosophy with the technical, mathematical details. As a bonus, the whole gamut of topics from philosophy and physics arise, including the nature of reality, emergence, Bohmian mechanics, Bell's Theorem, and more. We conclude with some analysis of Sean's speculative work on the concept of emergent spacetime, a viewpoint which naturally arises from Many Worlds. This video is most suitable for those with a basic technical understanding of quantum mechanics.
Part I: Introduction
00:00:00 : Introduction
00:05:42 : Philosophy and science: more interdisciplinary work?
00:09:14 : How Sean got interested in Many Worlds (MW)
00:13:04 : Technical outline
Part II: Quantum Mechanics in a Nutshell
00:14:58 : Textbook QM review
00:24:25 : The measurement problem
00:25:28 : Einstein: "God does not play dice"
00:27:49 : The reality problem
Part III: Many Worlds
00:31:53 : How MW comes in
00:34:28 : EPR paradox (original formulation)
00:40:58 : Simpler to work with spin
00:42:03 : Spin entanglement
00:44:46 : Decoherence
00:49:16 : System, observer, environment clarification for decoherence
00:53:54 : Density matrix perspective (sketch)
00:56:21 : Deriving the Born rule
00:59:09 : Everett: right answer, wrong reason. The easy and hard part of Born's rule.
01:03:33 : Self-locating uncertainty: which world am I in?
01:04:59 : Two arguments for Born rule credences
01:11:28 : Observer-system split: pointer-state problem
01:13:11 : Schrodinger's cat and decoherence
01:18:21 : Consciousness and perception
01:21:12 : Emergence and MW
01:28:06 : Sorites Paradox and are there infinitely many worlds
01:32:50 : Bad objection to MW: "It's not falsifiable."
Part IV: Additional Topics
01:35:13 : Bohmian mechanics
01:40:29 : Bell's Theorem. What the Nobel Prize committee got wrong
01:41:56 : David Deutsch on Bohmian mechanics
01:46:39 : Quantum mereology
01:49:09 : Path integral and double slit: virtual and distinct worlds
Part V. Emergent Spacetime
01:55:05 : Setup
02:02:42 : Algebraic geometry / functional analysis perspective
02:04:54 : Relation to MW
Part VI. Conclusion
02:07:16 : Distribution of QM beliefs
02:08:38 : Locality
Further reading:
Hugh Everett. The Theory of the Universal Wave Function, 1956.
Sean Carroll. Something Deeply Hidden, 2019.
More Sean Carroll & Timothy Nguyen:
Fragments of the IDW: Joe Rogan, Sam Harris, Eric Weinstein:
Twitter: @iamtimnguyen

Tuesday May 02, 2023

Daniel Schroeder is a particle and accelerator physicist and an editor for The American Journal of Physics. Dan received his PhD from Stanford University, where he spent most of his time at the Stanford Linear Accelerator, and he is currently a professor in the department of physics and astronomy at Weber State University. Dan is also the author of two revered physics textbooks, the first with Michael Peskin called An Introduction to Quantum Field Theory (or simply Peskin & Schroeder within the physics community) and the second An Introduction to Thermal Physics. Dan enjoys teaching physics courses at all levels, from Elementary Astronomy through Quantum Mechanics.
In this episode, I get to connect with one of my teachers, having taken both thermodynamics and quantum field theory courses when I was a university student based on Dan's textbooks. We take a deep dive towards answering two fundamental questions in the subject of thermodynamics: what is temperature and what is entropy? We provide both a qualitative and quantitative analysis, discussing good and bad definitions of temperature, microstates and macrostates, the second law of thermodynamics, and the relationship between temperature and entropy. Our discussion was also a great chance to shed light on some of the philosophical assumptions and conundrums in thermodynamics that do not typically come up in a physics course: the fundamental assumption of statistical mechanics, Laplace's demon, and the arrow of time problem (Loschmidt's paradox) arising from the second law of thermodynamics (i.e. why is entropy increasing in the future when mechanics has time-reversal symmetry).
00:00:00 : Introduction
00:01:54 : Writing Books
00:06:51 : Academic Track: Research vs Teaching
00:11:01 : Charming Book Snippets
00:14:54 : Discussion Plan: Two Basic Questions
00:17:19 : Temperature is What You Measure with a Thermometer
00:22:50 : Bad definition of Temperature: Measure of Average Kinetic Energy
00:25:17 : Equipartition Theorem
00:26:10 : Relaxation Time
00:27:55 : Entropy from Statistical Mechanics
00:30:12 : Einstein solid
00:32:43 : Microstates + Example Computation
00:38:33: Fundamental Assumption of Statistical Mechanics (FASM)
00:46:29 : Multiplicity is highly concentrated about its peak
00:49:50 : Entropy is Log(Multiplicity)
00:52:02 : The Second Law of Thermodynamics
00:56:13 : FASM based on our ignorance?
00:57:37 : Quantum Mechanics and Discretization
00:58:30 : More general mathematical notions of entropy
01:02:52 : Unscrambling an Egg and The Second Law of Thermodynamics
01:06:49 : Principle of Detailed Balance
01:09:52 : How important is FASM?
01:12:03 : Laplace's Demon
01:13:35 : The Arrow of Time (Loschmidt's Paradox)
01:15:20 : Comments on Resolution of Arrow of Time Problem
01:16:07 : Temperature revisited: The actual definition in terms of entropy
01:25:24 : Historical comments: Clausius, Boltzmann, Carnot
01:29:07 : Final Thoughts: Learning Thermodynamics
Further Reading:
Daniel Schroeder. An Introduction to Thermal Physics
L. Landau & E. Lifschitz. Statistical Physics.
Twitter: @iamtimnguyen

Tuesday Mar 21, 2023

Ethan Siegel is a theoretical astrophysicist and science communicator. He received his PhD from the University of Florida and held academic positions at the University of Arizona, University of Oregon, and Lewis & Clark College before moving on to become a full-time science writer. Ethan is the author of the book Beyond The Galaxy, which is the story of “How Humanity Looked Beyond Our Milky Way And Discovered The Entire Universe” and he has contributed numerous articles to ScienceBlogs, Forbes, and BigThink. Today, Ethan is the face and personality behind Starts With A Bang, both a website and podcast by the same name that is dedicated to explaining and exploring the deepest mysteries of the cosmos.
In this episode, Ethan and I discuss the mysterious nature of dark matter: the evidence for it and the proposals for what it might be.
Part I. Introduction
00:00:00 : Biography and path to science writing
00:07:26 : Keeping up with the field outside academia
00:11:42 : If you have a bone to pick with Ethan...
00:12:50 : On looking like a scientist and words of wisdom
00:18:24 : Understanding dark matter = one of the most important open problems
00:21:07 : Technical outline
Part II. Ordinary Matter
23:28 : Matter and radiation scaling relations
29:36 : Hubble constant
31:00 : Components of rho in Friedmann's equations
34:14 : Constituents of the universe
41:21 : Big Bang nucleosynthesis (BBN)
45:32 : eta: baryon to photon ratio and deuterium formation
53:15 : Mass ratios vs eta
Part III. Dark Matter
1:01:02 : rho = radiation + ordinary matter + dark matter + dark energy
1:05:25 : nature of peaks and valleys in cosmic microwave background (CMB): need dark matter
1:07:39: Fritz Zwicky and mass mismatch among galaxies of a cluster
1:10:40 : Kent Ford and Vera Rubin and and mass mismatch within a galaxy
1:11:56 : Recap: BBN tells us that only about 5% of matter is ordinary
1:15:55 : Concordance model (Lambda-CDM)
1:21:04 : Summary of how dark matter provides a common solution to many problems
1:23:29 : Brief remarks on modified gravity
1:24:39 : Bullet cluster as evidence for dark matter
1:31:40 : Candidates for dark matter (neutrinos, WIMPs, axions)
1:38:37 : Experiment vs theory. Giving up vs forging on
1:48:34 : Conclusion
Image Credits:
Further learning:
E. Siegel. Beyond the Galaxy
Ethan Siegel's webpage:
More Ethan Siegel & Timothy Nguyen videos:
Brian Keating’s Losing the Nobel Prize Makes a Good Point but …
Testing Eric Weinstein's and Stephen Wolfram's Theories of Everything
Twitter: @iamtimnguyenWebpage:

Wednesday Feb 15, 2023

Alex Kontorovich is a Professor of Mathematics at Rutgers University and served as the Distinguished Professor for the Public Dissemination of Mathematics at the National Museum of Mathematics in 2020–2021. Alex has received numerous awards for his illustrious mathematical career, including the Levi L. Conant Prize in 2013 for mathematical exposition, a Simons Foundation Fellowship, an NSF career award, and being elected Fellow of the American Mathematical Society in 2017. He currently serves on the Scientific Advisory Board of Quanta Magazine and as Editor-in-Chief of the Journal of Experimental Mathematics.
In this episode, Alex takes us from the ancient beginnings to the present day on the subject of circle packings. We start with the Problem of Apollonius on finding tangent circles using straight-edge and compass and continue forward in basic Euclidean geometry up until the time of Leibniz whereupon we encounter the first complete notion of a circle packing. From here, the plot thickens with observations on surprising number theoretic coincidences, which only received full appreciation through the craftsmanship of chemistry Nobel laureate Frederick Soddy. We continue on with more advanced mathematics arising from the confluence of geometry, group theory, and number theory, including fractals and their dimension, hyperbolic dynamics, Coxeter groups, and the local to global principle of advanced number theory. We conclude with a brief discussion on extensions to sphere packings.
I. Introduction
00:00: Biography
11:08: Lean and Formal Theorem Proving
13:05: Competitiveness and academia
15:02: Erdos and The Book
19:36: I am richer than Elon Musk
21:43: Overview
II. Setup
24:23: Triangles and tangent circles
27:10: The Problem of Apollonius
28:27: Circle inversion (Viette’s solution)
36:06: Hartshorne’s Euclidean geometry book: Minimal straight-edge & compass constructions
III. Circle Packings
41:49: Iterating tangent circles: Apollonian circle packing
43:22: History: Notebooks of Leibniz
45:05: Orientations (inside and outside of packing)
45:47: Asymptotics of circle packings
48:50: Fractals
50:54: Metacomment: Mathematical intuition
51:42: Naive dimension (of Cantor set and Sierpinski Triangle)
1:00:59: Rigorous definition of Hausdorff measure & dimension
IV. Simple Geometry and Number Theory
1:04:51: Descartes’s Theorem
1:05:58: Definition: bend = 1/radius
1:11:31: Computing the two bends in the Apollonian problem
1:15:00: Why integral bends?
1:15:40: Frederick Soddy: Nobel laureate in chemistry
1:17:12: Soddy’s observation: integral packings
V. Group Theory, Hyperbolic Dynamics, and Advanced Number Theory
1:22:02: Generating circle packings through repeated inversions (through dual circles)
1:29:09: Coxeter groups: Example
1:30:45: Coxeter groups: Definition
1:37:20: Poincare: Dynamics on hyperbolic space
1:39:18: Video demo: flows in hyperbolic space and circle packings
1:42:30: Integral representation of the Coxeter group
1:46:22: Indefinite quadratic forms and integer points of orthogonal groups
1:50:55: Admissible residue classes of bends
1:56:11: Why these residues? Answer: Strong approximation + Hasse principle
2:04:02: Major conjecture
2:06:02: The conjecture restores the "Local to Global" principle (for thin groups instead of orthogonal groups)
2:09:19: Confession: What a rich subject
2:10:00: Conjecture is asymptotically true
2:12:02: M. C. Escher
VI. Dimension Three: Sphere Packings
2:13:03: Setup + what Soddy built
2:15:57: Local to Global theorem holds
VII. Conclusion
2:18:20: Wrap up
2:19:02: Russian school vs Bourbaki
Image Credits:

Wednesday Jan 04, 2023

Greg Yang is a mathematician and AI researcher at Microsoft Research who for the past several years has done incredibly original theoretical work in the understanding of large artificial neural networks. Greg received his bachelors in mathematics from Harvard University in 2018 and while there won the Hoopes prize for best undergraduate thesis. He also received an Honorable Mention for the Morgan Prize for Outstanding Research in Mathematics by an Undergraduate Student in 2018 and was an invited speaker at the International Congress of Chinese Mathematicians in 2019.
In this episode, we get a sample of Greg's work, which goes under the name "Tensor Programs" and currently spans five highly technical papers. The route chosen to compress Tensor Programs into the scope of a conversational video is to place its main concepts under the umbrella of one larger, central, and time-tested idea: that of taking a large N limit. This occurs most famously in the Law of Large Numbers and the Central Limit Theorem, which then play a fundamental role in the branch of mathematics known as Random Matrix Theory (RMT). We review this foundational material and then show how Tensor Programs (TP) generalizes this classical work, offering new proofs of RMT. We conclude with the applications of Tensor Programs to a (rare!) rigorous theory of neural networks.
Part I. Introduction
00:00:00 : Biography
00:02:45 : Harvard hiatus 1: Becoming a DJ
00:07:40 : I really want to make AGI happen (back in 2012)
00:09:09 : Impressions of Harvard math
00:17:33 : Harvard hiatus 2: Math autodidact
00:22:05 : Friendship with Shing-Tung Yau
00:24:06 : Landing a job at Microsoft Research: Two Fields Medalists are all you need
00:26:13 : Technical intro: The Big Picture
00:28:12 : Whiteboard outline
Part II. Classical Probability Theory
00:37:03 : Law of Large Numbers
00:45:23 : Tensor Programs Preview
00:47:26 : Central Limit Theorem
00:56:55 : Proof of CLT: Moment method
1:00:20 : Moment method explicit computations
Part III. Random Matrix Theory
1:12:46 : Setup
1:16:55 : Moment method for RMT
1:21:21 : Wigner semicircle law
Part IV. Tensor Programs
1:31:03 : Segue using RMT
1:44:22 : TP punchline for RMT
1:46:22 : The Master Theorem (the key result of TP)
1:55:04 : Corollary: Reproof of RMT results
1:56:52 : General definition of a tensor program
Part V. Neural Networks and Machine Learning
2:09:05 : Feed forward neural network (3 layers) example
2:19:16 : Neural network Gaussian Process
2:23:59 : Many distinct large N limits for neural networks
2:27:24 : abc parametrizations (Note: "a" is absorbed into "c" here): variance and learning rate scalings
2:36:54 : Geometry of space of abc parametrizations
2:39:41: Kernel regime
2:41:32 : Neural tangent kernel
2:43:35: (No) feature learning
2:48:42 : Maximal feature learning
2:52:33 : Current problems with deep learning
2:55:02 : Hyperparameter transfer (muP)
3:00:31 : Wrap up
Further Reading:
Tensor Programs I, II, III, IV, V by Greg Yang and coauthors.
Twitter: @iamtimnguyen

Tuesday Nov 22, 2022

Scott Aaronson is a professor of computer science at University of Texas at Austin and director of its Quantum Information Center. Previously he received his PhD at UC Berkeley and was a faculty member at MIT in Electrical Engineering and Computer Science from 2007-2016. Scott has won numerous prizes for his research on quantum computing and complexity theory, including the Alan T Waterman award in 2012 and the ACM Prize in Computing in 2020. In addition to being a world class scientist, Scott is famous for his highly informative and entertaining blog Schtetl Optimized, which has kept the scientific community up to date on quantum hype for nearly the past two decades.
In this episode, Scott Aaronson gives a crash course on quantum computing, diving deep into the details, offering insights, and clarifying misconceptions surrounding quantum hype.
Correction: 59:03: The matrix denoted as "Hadamard gate" is actually a 45 degree rotation matrix. The Hadamard gate differs from this matrix by a sign flip in the last column. See 1:11:00 for the Hadamard gate.
Part I. Introduction (Personal)
00:00: Biography
01:02: Shtetl Optimized and the ways of blogging
09:56: sabattical at OpenAI, AI safety, machine learning
10:54: "I study what we can't do with computers we don't have"
Part II. Introduction (Technical)
22:57: Overview
24:13: SMBC Cartoon: "The Talk". Summary of misconceptions of the field
33:09: How all quantum algorithms work: choreograph pattern of interference
34:38: Outline
Part III. Setup
36:10: Review of classical bits
40:46: Tensor product and computational basis
42:07: Entanglement
44:25: What is not spooky action at a distance
46:15: Definition of qubit
48:10: bra and ket notation
50:48: Superposition example
52:41: Measurement, Copenhagen interpretation
Part IV. Working with qubits
57:02: Unitary operators, quantum gates
1:03:34: Philosophical aside: How to "store" 2^1000 bits of information.
1:08:34: CNOT operation
1:09:45: quantum circuits
1:11:00: Hadamard gate
1:12:43: circuit notation, XOR notation
1:14:55: Subtlety on preparing quantum states
1:16:32: Building and decomposing general quantum circuits: Universality
1:21:30: Complexity of circuits vs algorithms
1:28:45: How quantum algorithms are physically implemented
1:31:55: Equivalence to quantum Turing Machine
Part V. Quantum Speedup
1:35:48: Query complexity (black box / oracle model)
1:39:03: Objection: how is quantum querying not cheating?
1:42:51: Defining a quantum black box
1:45:30: Efficient classical f yields efficient U_f
1:47:26: Toffoli gate
1:50:07: Garbage and quantum uncomputing
1:54:45: Implementing (-1)^f(x))
1:57:54: Deutsch-Jozsa algorithm: Where quantum beats classical
2:07:08: The point: constructive and destructive interference
Part VI. Complexity Classes
2:08:41: Recap. History of Simon's and Shor's Algorithm
2:14:42: BQP
2:18:18: EQP
2:20:50: P
2:22:28: NP
2:26:10: P vs NP and NP-completeness
2:33:48: P vs BQP
2:40:48: NP vs BQP
2:41:23: Where quantum computing explanations go off the rails
Part VII. Quantum Supremacy
2:43:46: Scalable quantum computing
2:47:43: Quantum supremacy
2:51:37: Boson sampling
2:52:03: What Google did and the difficulties with evaluating supremacy
3:04:22: Huge open question
Twitter: @IAmTimNguyen

Thursday Oct 13, 2022

Grant Sanderson is a mathematician who is the author of the YouTube channel “3Blue1Brown”, viewed by millions for its beautiful blend of visual animation and mathematical pedagogy. His channel covers a wide range of mathematical topics, which to name a few include calculus, quaternions, epidemic modeling, and artificial neural networks. Grant received his bachelor's degree in mathematics from Stanford University and has worked with a variety of mathematics educators and outlets, including Khan Academy, The Art of Problem Solving, MIT OpenCourseWare, Numberphile, and Quanta Magazine.
In this episode, we discuss the famous unsolvability of quintic polynomials: there exists no formula, consisting only of finitely many arithmetic operations and radicals, for expressing the roots of a general fifth degree polynomial in terms of the polynomial's coefficients. The standard proof that is taught in abstract algebra courses uses the machinery of Galois theory. Instead of following that route, Grant and I proceed in barebones style along (somewhat) historical lines by first solving quadratics, cubics, and quartics. Along the way, we present the insights obtained by Lagrange that motivate a very natural combinatorial question, which contains the germs of modern group theory and Galois theory and whose answer suggests that the quintic is unsolvable (later confirmed through the work of Abel and Galois). We end with some informal discussions about Abel's proof and the topological proof due to Vladimir Arnold.
Part I. Introduction
00:52: How did you get interested in math?
06:30: Future of math pedagogy and AI 
12:03: Overview. How Grant got interested in unsolvability of the quintic
15:26: Problem formulation
17:42: History of solving polynomial equations
19:50: Po-Shen Loh 
Part II. Working Up to the Quintic
28:06: Quadratics
34:38 : Cubics
37:20: Viete’s formulas
48:51: Math duels over solving cubics: del Ferro, Fiorre, Tartaglia, Cardano, Ferrari
53:24: Prose poetry of solving cubics
54:30: Cardano’s Formula derivation
1:03:22: Resolvent 
1:04:10: Why exactly 3 roots from Cardano’s formula?
Part III. Thinking More Systematically
1:12:25: Takeaways and Lagrange’s insight into why quintic might be unsolvable
1:17:20: Origins of group theory?
1:23:29: History’s First Whiff of Galois Theory
1:25:24: Fundamental Theorem of Symmetric Polynomials
1:30:18: Solving the quartic from the resolvent
1:40:08: Recap of overall logic
Part IV. Unsolvability of the Quintic
1:52:30: S_5 and A_5 group actions
2:01:18: Lagrange’s approach fails!
2:04:01: Abel’s proof
2:06:16: Arnold’s Topological Proof
2:18:22: Closing Remarks
Further Reading on Arnold's Topological Proof of Unsolvability of the Quintic:
L. Goldmakher.
B. Katz.
Twitter: @iamtimnguyen

Wednesday Sep 07, 2022

John Baez is a mathematical physicist, professor of mathematics at UC Riverside, a researcher at the Centre for Quantum Technologies in Singapore, and a researcher at the Topos Institute in Berkeley, CA. John has worked on an impressively wide range of topics, pure and applied, ranging from loop quantum gravity, applications of higher categories to physics, applied category theory, environmental issues and math related to engineering and biology, and most recently on applying network theory to scientific software.Additionally, John is a prolific writer and blogger. This first began with John’s column This Week's Finds in Mathematical Physics, which ran 300 issues between 1993 and 2010, which then continued in the form of his ongoing blog Azimuth. Last but not least, John is also a host and contributor of the popular blog The n-category Cafe.
In this episode, we dive into John Baez and John Huerta’s paper “The Algebra of Grand Unified Theories” which was awarded the Levi Conant Prize in 2013. The paper gives a crash course in the representation theory underlying the Standard Model of particle physics and its three most well known Grand Unified Theories (GUTs): the SU(5), SO(10) (aka Spin(10)), and Pati-Salam theories. The main result of Baez-Huerta is that the particle representations underlying the three GUTs can in fact be unified via a commutative diagram. We dive deep into the numerology of the standard model to see how the SU(5) theory naturally arises. We then make brief remarks about SO(10) and Pati-Salam theories in order to state the Baez-Huerta theorem about their organization into a commutative square: a unification among grand unifications!
1:29:01: The formula for hypercharge in the bottom right note should be Y = 2(Q-I_3) instead of Y = (Q-I_3)/2.
While we do provide a crash course on SU(2) and spin, some representation theory jargon is used at times in our discussion. Those unfamiliar should just forge ahead!
We work in Euclidean signature instead of Lorentzian signature. Other than keeping track of minus signs, no essential details are changed. 
Part I. Introduction
00:00: Introduction
05:50: Climate change
09:40: Crackpot index
14:50: Eric Weinstein, Brian Keating, Geometric Unity
18:13: Overview of “The Algebra of Grand Unified Theories” paper
25:40: Overview of Standard Model and GUTs
34:25: SU(2), spin, isospin of nucleons 40:22: SO(4), Spin(4), double cover
44:24: three kinds of spin
Part II. Zoology of Standard Model
49:35: electron and neutrino
58:40: quarks
1:04:51: the three generations of the Standard Model
1:08:25: isospin quantum numbers
1:17:11: U(1) representations (“charge”)
1:29:01: hypercharge
1:34:00: strong force and color
1:36:50: SU(3)
1:40:45: antiparticles
Part III. SU(5) numerology
1:41:16: 32 = 2^5 particles
1:45:05: Mapping SU(3) x SU(2) x U(1) to SU(5) and hypercharge matching
2:05:17: Exterior algebra of C^5 and more hypercharge matching
2:37:32: SU(5) rep extends Standard Model rep
Part IV. How the GUTs fit together
2:41:42: SO(10) rep: brief remarks
2:46:28: Pati-Salam rep: brief remarks
2:47:17: Commutative diagram: main result
2:49:12: What about the physics? Spontaneous symmetry breaking and the Higgs mechanism
Twitter: @iamtimnguyen

Sunday Aug 21, 2022

Tai-Danae Bradley is a mathematician who received her Ph.D. in mathematics from the CUNY Graduate Center. She was formerly at Alphabet and is now at Sandbox AQ, a startup focused on combining machine learning and quantum physics. Tai-Danae is a visiting research professor of mathematics at The Master’s University and the executive director of the Math3ma Institute, where she hosts her popular blog on category theory. She is also a co-author of the textbook Topology: A Categorical Approach that presents basic topology from the modern perspective of category theory.
In this episode, we provide a compressed crash course in category theory. We provide definitions and plenty of basic examples for all the basic notions: objects, morphisms, categories, functors, natural transformations. We also discuss the first basic result in category theory which is the Yoneda Lemma. We conclude with a discussion of how Tai-Danae has used category-theoretic methods in her work on language modeling, in particular, in how the passing from syntax to semantics can be realized through category-theoretic notions.
Originally published on July 20, 2022 on YouTube:
00:00:00 : Introduction
00:03:07 : How did you get into category theory?
00:06:29 : Outline of podcast
00:09:21 : Motivating category theory
00:11:35 : Analogy: Object Oriented Programming
00:12:32 : Definition of category
00:18:50 : Example: Category of sets
00:20:17 : Example: Matrix category
00:25:45 : Example: Preordered set (poset) is a category
00:33:43 : Example: Category of finite-dimensional vector spaces
00:37:46 : Forgetful functor
00:39:15 : Fruity example of forgetful functor: Forget race, gender, we're all part of humanity!
00:40:06 : Definition of functor
00:42:01 : Example: API change between programming languages is a functor
00:44:23 : Example: Groups, group homomorphisms are categories and functors
00:47:33 : Resume definition of functor
00:49:14 : Example: Functor between poset categories = order-preserving function
00:52:28 : Hom Functors. Things are getting meta (no not the tech company)
00:57:27 : Category theory is beautiful because of its rigidity
01:00:54 : Contravariant functor
01:03:23 : Definition: Presheaf
01:04:04 : Why are things meta? Arrows, arrows between arrows, categories of categories, ad infinitum.
01:07:38 : Probing a space with maps (prelude to Yoneda Lemma)
01:12:10 : Algebraic topology motivated category theory
01:15:44 : Definition: Natural transformation
01:19:21 : Example: Indexing category
01:21:54 : Example: Change of currency as natural transformation
01:25:35 : Isomorphism and natural isomorphism
01:27:34 : Notion of isomorphism in different categories
01:30:00 : Yoneda Lemma
01:33:46 : Example for Yoneda Lemma: Identity functor and evaluation natural transformation
01:42:33 : Analogy between Yoneda Lemma and linear algebra
01:46:06 : Corollary of Yoneda Lemma: Isomorphism of objects = Isomorphism of hom functors
01:50:40 : Yoneda embedding is fully faithful. Reasoning about this.
01:55:15 : Language Category
02:03:10 : Tai-Danae's paper: "An enriched category theory of language: from syntax to semantics"
Further Reading:
Tai-Danae's Blog:
Tai-Danae Bradley. "What is applied category theory?"
Tai-Danae Bradley, John Terilla, Yiannis Vlassopoulos. "An enriched category theory of language: from syntax to semantics."

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