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Computational complexity theorists argue that semiclassical gravity's non-linear dynamics would enable impossibly powerful computation, proving gravity must be quantized. The paper uses the Schrödinger-Newton equation to show that classical gravity coupled to quantum matter leads to computational contradictions.
This paper argues that under semiclassical gravity, a massive qubit can solve NP-complete problems in polynomial time via nonlinear dynamics, implying gravity must be quantized.
This paper introduces a quantitative notion of diversity of extensions in abstract argumentation based on symmetric difference, and provides a systematic complexity classification for related reasoning tasks.
A social media post explaining the P vs NP problem by comparing NP to a 'magical computer' that always finds the right path, referencing MIT's Introduction to Algorithms course.
This paper extends the study of computational hardness in learning robust classifiers, showing that efficient robust classification can be impossible even when unbounded robust classifiers exist, and establishing a win-win result: either an efficient robust classifier can be learned, or new cryptographic primitives can be constructed.