Algorithmic Randomness and Kolmogorov Complexity for Qubits
Tejas Bhojraj

TL;DR
This paper explores quantum analogues of classical randomness concepts, establishing equivalences and differences between various quantum randomness notions, and analyzing their implications for quantum information theory and computability.
Contribution
It introduces quantum versions of Solovay and Schnorr randomness, establishes their equivalence with quantum Martin-Löf randomness, and investigates their properties and relations to quantum complexity measures.
Findings
Quantum Solovay randomness is equivalent to quantum Martin-Löf randomness.
Quantum Schnorr randomness satisfies a quantum law of large numbers.
Classical randomness can be generated from computable quantum states.
Abstract
Nies and Scholz defined quantum Martin-L\"of randomness (q-MLR) for states (infinite qubitstrings). We define a notion of quantum Solovay randomness and show it to be equivalent to q-MLR using purely linear algebraic methods. Quantum Schnorr randomness is then introduced. A quantum analogue of the law of large numbers is shown to hold for quantum Schnorr random states. We introduce quantum-K, () a measure of the descriptive complexity of density matrices using classical prefix-free Turing machines and show that the initial segments of weak Solovay random and quantum Schnorr random states are incompressible in the sense of . Several connections between Solovay randomness and carry over to those between weak Solovay randomness and . We then define , using computable measure machines and connect it to quantum Schnorr randomness. We then explore a notion of `measuring'…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Quantum Computing Algorithms and Architecture · Cellular Automata and Applications
