3,006 research outputs found

    Causal Inference by Stochastic Complexity

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    The algorithmic Markov condition states that the most likely causal direction between two random variables X and Y can be identified as that direction with the lowest Kolmogorov complexity. Due to the halting problem, however, this notion is not computable. We hence propose to do causal inference by stochastic complexity. That is, we propose to approximate Kolmogorov complexity via the Minimum Description Length (MDL) principle, using a score that is mini-max optimal with regard to the model class under consideration. This means that even in an adversarial setting, such as when the true distribution is not in this class, we still obtain the optimal encoding for the data relative to the class. We instantiate this framework, which we call CISC, for pairs of univariate discrete variables, using the class of multinomial distributions. Experiments show that CISC is highly accurate on synthetic, benchmark, as well as real-world data, outperforming the state of the art by a margin, and scales extremely well with regard to sample and domain sizes

    Quantum discord in a spin system with symmetry breaking

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    We analyze the quantum discord Q throughout the low-temperature phase diagram of the quantum XY model in transverse field. We first focus on the T=0 order-disorder quantum phase transition both in the symmetric ground state and in the symmetry broken one. Besides it, we highlight how Q displays clear anomalies also at a non critical value of the control parameter inside the ordered phase, where the ground state is completely factorized. We evidence how the phenomenon is in fact of collective nature and displays universal features. We also study Q at finite temperature. We show that, close to the quantum phase transition, Q exhibits quantum-classical crossover of the system with universal scaling behavior. We evidence a non trivial pattern of thermal correlations resulting from the factorization phenomenon.Comment: 9 pages, 9 figure, Contribution to the Festschrift volume in honour of Vladimir Korepi

    Nonclassical stochastic flows and continuous products

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    Contrary to the classical wisdom, processes with independent values (defined properly) are much more diverse than white noise combined with Poisson point processes, and product systems are much more diverse than Fock spaces. This text is a survey of recent progress in constructing and investigating nonclassical stochastic flows and continuous products of probability spaces and Hilbert spaces.Comment: A survey, 126 pages. Version 3 (final): former Question 9d4 is solved; 8a1 reformulated. Ref [41] added. For readability, sections are reordered (123456..->142536..). Cosmetic changes, mostly in 1b, 2a, 3d, (4a7) (v3 numbers) and Introductio
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