Luna Lima Keller

What I do

Quantum computers can draw on resources unavailable to classical computers, some famous resources are superposition and entanglement. Yet these familiar quantum features do not, on their own, guarantee a computational advantage. For example, a family of quantum states known as stabilizer states can exhibit both, while still not adding enough power to outmatch classical algorithms.

My research focuses on a resource that takes us beyond this restricted setting: non-stabilizerness, more playfully known as magic. It helps explain what quantum computers need to tackle problems beyond the reach of classical machines. Despite its name, magic is a precisely defined mathematical concept, with no connection to spells or fairy tales. Nevertheless, it captures something fascinating about the quantum world, and we are still uncovering how it gives quantum computation its power.

One question that motivates my work is how much we can learn about a quantum system from only a small amount of information. Describing every detail quickly becomes impractical as the system grows, so I look for ways to detect and quantify magic using a limited set of measurements. It is a little like trying to recognize a picture from a few carefully chosen details: which parts should we look at, and what can we confidently conclude from them? For me, finding ways to answer these questions connects abstract mathematics with the practical challenge of understanding quantum devices.

Why it matters

What fascinates me most is exploring the boundary between quantum and classical computing. We still have much to learn about where that boundary lies: a task that seems beyond the reach of classical computers may become manageable with a clever new algorithm. Researchers are constantly pushing these limits, while quantum computing scientists work to identify tasks where quantum computers can demonstrably do better. Each side challenges the other to sharpen its ideas and reconsider what is possible.

This is a competition in which everyone wins. Finding a classical solution to a supposedly difficult quantum problem is itself a valuable discovery: it gives us new methods and helps clarify where quantum resources are truly needed. Likewise, understanding the limitations of classical computers helps guide the development of quantum algorithms. I find this exchange especially exciting because its value reaches beyond future technology. It can inspire tools for the computers we already use, while helping us understand what we might achieve with the quantum computers we are working to build.