Fidget is a library for representing, compiling, and evaluating large-scale math expressions, i.e. hundreds or thousands of arithmetic clauses. It's mainly designed as a backend for implicit surfaces, but the library is flexible enough for many different uses!
Qalculate! - the ultimate desktop calculator
KaTeX – The fastest math typesetting library for the web
Simple API, no dependencies – yet super fast on all major browsers.
Tangible Functional Programming
Regnestykker
Sheets with calculus exercises suitable for kids that are learning the first basic arithmetic operations.
Calculating with lenses | Proceedings of the 20th ACM SIGPLAN workshop on Partial evaluation and program manipulation
Functional programs are particularly well suited to formal manipulation by equational reasoning. In particular, it is straightforward to use calculational methods for program transformation. Well-known transformation techniques, like tupling or the ...
J Notation as a Tool of Thought
Kenneth Iverson’s 1964 language, APL, won him the Turing Award. His award lecture, Notation as a Tool of Thought, argued that better notations would lead people to deeper insights about mathematics. He provided a number of examples ranging across linear algebra, arithmetic, probability, and logic. Unfortunately, most of the mathematics he covers isn’t relevant to programming. However, his core idea still applies, and changing how we describe programs changes how we think about them.
Times Tables — Learn, Play and Print the Multiplication Tables
Practise every times table from 1 to 12 with free games, speed tests, printable charts and worksheets. Works on phones, tablets and computers. No sign-up.
About - Project Euler
A website dedicated to the fascinating world of mathematics and programming
Uri Bram 🔍 on Twitter / X
So I got memed into trying MathAcademy and it was one of the weirdest product experiences of my life. In short: I think they have an amazing product, but they're very opinionated about how you use it, and as a result I can't use it at all.Basically: they've figured out some…— Uri Bram 🔍 (@UriBram) January 16, 2025
Embracing AI and formalization: Experimenting with tomorrow’s mathematical tools
Embracing AI and formalization: Experimenting with tomorrow’s mathematical tools. By Jarod Alper
Old and new apps, via modern coding agents
I have been interested in machine-assisted ways to do and teach mathematics from as far back as 1999, when I started coding several applets in Java 1.0, both for my complex analysis and linear alge…
Issue 084: Spreadsheets
Welcome to the 84th issue of De Programmatica Ipsum, about Spreadsheets. In this edition, we declare spreadsheets the most popular software programming environment of all time; in the Library section, we learn how to use Lotus 1-2-3 for science reading "Spreadsheet Physics" by Charles Misner and Patrick Cooney; and in our Vidéothèque section, we discover that Excel is a Turing-complete, functional programming language through the eyes of Dr. Felienne Hermans.
I love calculator
The other day I was randomly browsing in a bookstore and stumbled by Empire of the Sum: The Rise and Reign of the Pocket Calculator. As I was flipping through its pages, a realization dawned on me with some force: I... love... calculator. I don't mean as a physical device that you would wish to purchase and use today. I mean as a product of technology and a symbol of a kind of philosophy. Behold:
All elementary functions from a single binary operator
A single two-input gate suffices for all of Boolean logic in digital hardware. No comparable primitive has been known for continuous mathematics: computing elementary functions such as sin, cos, sqrt, and log has always required multiple distinct operations. Here I show that a single binary operator, eml(x,y)=exp(x)-ln(y), together with the constant 1, generates the standard repertoire of a scientific calculator. This includes constants such as e, pi, and i; arithmetic operations including addition, subtraction, multiplication, division, and exponentiation as well as the usual transcendental and algebraic functions. For example, exp(x)=eml(x,1), ln(x)=eml(1,eml(eml(1,x),1)), and likewise for all other operations. That such an operator exists was not anticipated; I found it by systematic exhaustive search and established constructively that it suffices for the concrete scientific-calculator basis. In EML (Exp-Minus-Log) form, every such expression becomes a binary tree of identical nodes, yielding a grammar as simple as S -> 1 | eml(S,S). This uniform structure also enables gradient-based symbolic regression: using EML trees as trainable circuits with standard optimizers (Adam), I demonstrate the feasibility of exact recovery of closed-form elementary functions from numerical data at shallow tree depths up to 4. The same architecture can fit arbitrary data, but when the generating law is elementary, it may recover the exact formula.
It Is Fun to Pretend That Hard Things Are Easy!
A new online math platform promises to teach math 4x faster. Here is how!
