
Show Notes
We know all about how things exist in the three dimensions of length, width, and height. Physicists often talk about time as a fourth dimension, but what if there were a fourth spatial dimension — another direction entirely? How on earth would we picture that?
Mathematicians use topology to visualize abstract spaces in higher dimensions. Maggie Miller at the University of Texas at Austin explores what happens when knots encounter an extra dimension. Familiar tangled loops behave in unexpectedly complex and counterintuitive ways in 4D: Knots can always come undone, while ordinary surfaces like spheres can — surprisingly — become knotted in ways that can’t be undone.
In this episode, Miller explains to co-host Janna Levin why 4D is the lowest dimension that mathematicians still don’t fully understand, how she and her collaborators resolved a question about knotted surfaces first posed by mathematician Charles Livingston in 1982, and how her interest in art has helped her develop the visual techniques she uses to picture 4D spaces.
More from The Joy of Why
People may think of soil as just dirt, but it is anything but inert. Beneath your feet, a vast network of mycorrhizal fungi is hard at work, trading minerals with plant roots. This trading system helps enrich the soil, and it sequesters 13 billion tons of atmospheric carbon dioxide each year — roughly equivalent to one-third of the world’s fossil-fuel emissions. Scientists know that these fungi form partnerships with 80% of all plant species on Earth, a relationship that evolved some 450 million years ago. What they have not understood is how organisms with no brain or central nervous system can decide whom to trade with, and on what terms.
Quantum mechanics may be one of the most precisely tested paradigms in science, but there’s still no universally accepted interpretation of what it tells us about reality. How do we get from the wave-like behavior of quantum systems to the solid, macroscopic world of objects and the universe at large?
Mathematicians are witnessing a profound shift in their field. AI systems are now producing proofs, spotting connections between distant fields, and, in a few cases, solving problems that had stumped mathematicians for decades. The pace of progress over the past several months has raised challenging questions: What can AI systems actually do? And what happens to the more human, creative aspects of the field once machines can match – or exceed – people at problem-solving?
When an LLM answers a question, is it reasoning like humans, or just producing text that looks like reasoning? The distinction isn’t just philosophical, this determines what we can trust AI to do, how closely we need to supervise it, and ultimately what its real-world impact will turn out to be.
Pain and pleasure seem like simple facts of life, but they are far from it. Neuroscientists still cannot say why physical pain differs from psychological pain, for instance, nor why a loved one’s touch soothes while a stranger’s touch repels.