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Related papers: Assumptions of Randomness in Cosmology Models

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As physics searches for invariants in observations, this paper looks for invariants of probabilistic observation without assuming physical structure. Structure emerges from the basic assumption of science that new information shall lead to…

Quantum Physics · Physics 2007-05-23 Johann Summhammer

Questions such as whether we live in a spatially finite universe, and what its shape and size may be, are among the fundamental open problems that high precision modern cosmology needs to resolve. These questions go beyond the scope of…

Astrophysics · Physics 2007-05-23 M. J. Reboucas , G. I. Gomero

Inferring causal models from observed correlations is a challenging task, crucial to many areas of science. In order to alleviate the computational effort when sifting through possible causal explanations for some given observations, it is…

Provided a random realization of the cosmological model, observations of our cosmic neighborhood now allow us to build simulations of the latter down to the non-linear threshold. The resulting local Universe models are thus accurate up to a…

Cosmology and Nongalactic Astrophysics · Physics 2020-06-10 Jenny G. Sorce

Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge. A central issue is what defines a 'good' model. When addressing global properties of the…

History and Philosophy of Physics · Physics 2018-12-12 Martin Sahlén

There is increasing evidence that the universe may have a small cosmological constant. We suggest a scheme for naturally generating a small cosmological constant. Our idea requires the presence of a discrete accidental symmetry which is…

High Energy Physics - Phenomenology · Physics 2015-06-25 W. D. Garretson , E. D. Carlson

We consider global optimization problems, where the feasible region $\X$ is a compact subset of $\mathbb{R}^d$ with $d \geq 10$. For these problems, we demonstrate the following. First: the actual convergence of global random search…

Optimization and Control · Mathematics 2023-02-27 Jack Noonan , Anatoly Zhigljavsky

In order to account for the observable Universe, any comprehensive theory or model of cosmology must draw from many disciplines of physics, including gauge theories of strong and weak interactions, the hydrodynamics and microphysics of…

General Relativity and Quantum Cosmology · Physics 2015-06-25 Peter Anninos

When a group acts on a set, it naturally partitions it into orbits, giving rise to orbit problems. These are natural algorithmic problems, as symmetries are central in numerous questions and structures in physics, mathematics, computer…

Computational Complexity · Computer Science 2025-10-14 Peter Bürgisser , Mahmut Levent Doğan , Visu Makam , Michael Walter , Avi Wigderson

In contrast with software-generated randomness (called pseudo-randomness), quantum randomness is provable incomputable, i.e.\ it is not exactly reproducible by any algorithm. We provide experimental evidence of incomputability --- an…

Quantum Physics · Physics 2010-08-09 Cristian S. Calude , Michael J. Dinneen , Monica Dumitrescu , Karl Svozil

We study computing geometric problems on uncertain points. An uncertain point is a point that does not have a fixed location, but rather is described by a probability distribution. When these probability distributions are restricted to a…

Computational Geometry · Computer Science 2012-05-03 Allan Jorgensen , Maarten Löffler , Jeff M. Phillips

We demonstrate a fundamental relation between the structures of physical space and of quantum theory: the set of quantum correlations in a rotational prepare-and-measure scenario can be derived from covariance alone, without assuming…

Quantum Physics · Physics 2026-01-21 Caroline L. Jones , Stefan L. Ludescher , Albert Aloy , Markus P. Mueller

The proof of the theorem, which states that the Euclidean metric on the set of random points in an $n$-dimensional Euclidean space with the distribution of a special class, converges in probability in the limit $n\rightarrow\infty$ to the…

Mathematical Physics · Physics 2014-04-22 Alexander P. Zubarev

We construct universal prediction systems in the spirit of Popper's falsifiability and Kolmogorov complexity and randomness. These prediction systems do not depend on any statistical assumptions (but under the IID assumption they dominate,…

Machine Learning · Computer Science 2017-04-05 Vladimir Vovk , Dusko Pavlovic

It has been proposed that the observed dark energy can be explained away by the effect of large-scale nonlinear inhomogeneities. In the present paper we discuss how observations constrain cosmological models featuring large voids. We start…

Cosmology and Nongalactic Astrophysics · Physics 2015-03-18 Valerio Marra , Alessio Notari

Algorithmic theories of randomness can be related to theories of probabilistic sequence prediction through the notion of a predictor, defined as a function which supplies lower bounds on initial-segment probabilities of infinite sequences.…

Information Theory · Computer Science 2024-01-25 Lenhart K. Schubert

The probability distribution P from which the history of our universe is sampled represents a theory of everything or TOE. We assume P is formally describable. Since most (uncountably many) distributions are not, this imposes a strong…

Quantum Physics · Physics 2007-05-23 Juergen Schmidhuber

There is a deep cosmological mystery: although dependent on very different underlying physics, the timescales of structure formation, of galaxy cooling (both radiatively and against the CMB), and of vacuum domination do not differ by many…

High Energy Physics - Theory · Physics 2009-09-24 Raphael Bousso , Lawrence J. Hall , Yasunori Nomura

We discuss inhomogeneous cosmological models which satisfy the Copernican principle. We construct some inhomogeneous cosmological models starting from the ansatz that the all the observers in the models view an isotropic cosmic microwave…

General Relativity and Quantum Cosmology · Physics 2015-06-25 C. A. Clarkson , A. A. Coley , E. S. D. O'Neill , R. A. Sussman , R. K. Barrett

Most of the methods that produce space weather forecasts are based on deterministic models. In order to generate a probabilistic forecast, a model needs to be run several times sampling the input parameter space, in order to generate an…

Space Physics · Physics 2019-05-01 Enrico Camporeale , Xiangning Chu , Oleksiy Agapitov , Jacob Bortnik