What would it take to turn the entire cosmos into software-down to the rules that generate space and time? For decades, the simulation hypothesis has resided comfortably in the gap between philosophy and science fiction, buoyed by the simple intuition that if minds can build computers and computers can model worlds, then perhaps worlds can contain computers that model worlds in an endless nest. A group of researchers associated with the University of British Columbia Okanagan has tried treating that intuition as a technical claim rather than a vibe and argues that it fails for reasons rooted in logic rather than computing power.
In the present form, the simulation idea is framed through the same modern physics lens that already makes reality feel “digital”: proposals for quantum gravity generally treat spacetime as emergent, with its underlying substrate taking on a likeness to information. That framing has gained adherents in part because it reflects a vital enduring engineering metaphor: zoom in far enough and a smooth surface can reveal a grain. It’s even taken some quantum gravity efforts to the extent of casting the hunt for that “grain” as an experimental program in pursuit of would-be signatures of discreteness at scales far larger than the Planck length-a length on the order of 10−18 meters-using precision interferometry concepts.
Faizal’s group takes a different road: instead of searching for spacetime pixels, it asks whether a computational description could ever be complete. The key tool is Gödel’s incompleteness theorem-a result that limits what any sufficiently rich formal system can prove about itself. In the authors’ view, the same kind of limitation applies when computation is asked to serve as the foundation of a “theory of everything.” As Faizal puts it, “We have demonstrated that it is impossible to describe all aspects of physical reality using a computational theory of quantum gravity.”
The argument hinges on a distinction that tends to get flattened in the popular talk of simulations, where a simulation by definition runs on an algorithm: explicit rules that generate every allowed outcome. But the paper claims that any attempt to encode all of physics into such rules runs into statements that are true yet unreachable from within the computational framework. “Therefore, no physically complete and consistent theory of everything can be derived from computation alone,” Faizal adds, pointing instead to what the authors call “non-algorithmic understanding” content that can’t be captured as executable steps.
That claim also reframes why “information-first” physics does not necessarily imply “computable-first” reality. Even if spacetime and gravity arise out of deeper informational structure, the paper argues that its deepest layer cannot be fully described by algorithms. That removes the usual escape hatch: simulate the substrate, not just the surface. “Drawing upon mathematical theorems related to incompleteness and indefinability, we show that a fully consistent and complete description of reality cannot be accomplished via computation alone,” Faizal says. “It requires understanding in a nonalgorithmic way, which by definition is beyond algorithmic computation and therefore cannot be simulated. Hence, this universe cannot be a simulation.”
Co-author Dr. Lawrence M. Krauss ties the conclusion to a common aspiration in theoretical physics: deriving all phenomena from a compact set of rules. “The fundamental laws of physics cannot be contained within space and time, because they generate them,” he concludes, but adds that “a complete and consistent description of reality requires something deeper a form of understanding known as non-algorithmic understanding.”
In practice, the sharper contribution of the paper is not a cinematic takedown of The Matrix, but rather a boundary condition on a certain engineering dream: that reality can be fully reduced to a runnable specification. The universe may yet be describable in computationally useful ways. The claim here is that usefulness and completeness are not the same target.
