Scientific American reports that the 2026 Fields Medals went to four mathematicians for work ranging from the theory of knots to the motion of fluid: The Fields Medals went to Hong Wang of New York University and France's Institute of Advanced Scientific Studies (IHES), Yu Deng of the University of Chicago, John Pardon of Stony Brook University and Jacob Tsimerman of the University of Toronto. In the awards' 90-year history, Wang is only the third woman to win one, after mathematicians Maryam Mirzakhani and Maryna Viazovska in 2014 and 2022, respectively. Wang and Deng represent the prizes' only Chinese-born recipients besides mathematician Shing-Tung Yau, who won a Fields Medal in 1982. Hong Wang co-proved the three-dimensional Kakeya conjecture, establishing a fundamental limit on how little space is needed to rotate a line through every possible direction. Mathematician Nets Katz called it the field's "holy grail" problem and said the achievement made her "a central figure" in the area. Yu Deng and his collaborators reconciled the microscopic and macroscopic mathematics of fluid motion, proving that equations describing chaotic molecular interactions and large-scale fluid behavior are fundamentally connected. N.Y.U. mathematician Scott Armstrong called it "a truly spectacular, singular result." John Pardon made an early breakthrough in knot theory by proving that certain sequences of knots can have arbitrarily large "distortion," a measure of how difficult they are to traverse. Princeton mathematician David Gabai said the problem had "attracted much interest among mathematicians during the previous 25 years." Jacob Tsimerman and two collaborators proved the Andre-Oort conjecture, giving mathematicians a stronger way to understand special points on complex geometric objects known as Shimura varieties. Collaborator Jonathan Pila described him as "a brilliant mathematician" known for his "brilliance and resourcefulness." Tsimerman has also advanced Hodge theory and hopes pure mathematics can help researchers better understand AI.Read more of this story at Slashdot.