1,331 research outputs found

    Physical Complexity of Symbolic Sequences

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    A practical measure for the complexity of sequences of symbols (``strings'') is introduced that is rooted in automata theory but avoids the problems of Kolmogorov-Chaitin complexity. This physical complexity can be estimated for ensembles of sequences, for which it reverts to the difference between the maximal entropy of the ensemble and the actual entropy given the specific environment within which the sequence is to be interpreted. Thus, the physical complexity measures the amount of information about the environment that is coded in the sequence, and is conditional on such an environment. In practice, an estimate of the complexity of a string can be obtained by counting the number of loci per string that are fixed in the ensemble, while the volatile positions represent, again with respect to the environment, randomness. We apply this measure to tRNA sequence data.Comment: 12 pages LaTeX2e, 3 postscript figures, uses elsart.cls. Substantially improved and clarified version, includes application to EMBL tRNA sequence dat

    Order in glassy systems

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    A directly measurable correlation length may be defined for systems having a two-step relaxation, based on the geometric properties of density profile that remains after averaging out the fast motion. We argue that the length diverges if and when the slow timescale diverges, whatever the microscopic mechanism at the origin of the slowing down. Measuring the length amounts to determining explicitly the complexity from the observed particle configurations. One may compute in the same way the Renyi complexities K_q, their relative behavior for different q characterizes the mechanism underlying the transition. In particular, the 'Random First Order' scenario predicts that in the glass phase K_q=0 for q>x, and K_q>0 for q<x, with x the Parisi parameter. The hypothesis of a nonequilibrium effective temperature may also be directly tested directly from configurations.Comment: Typos corrected, clarifications adde

    Safe and Complete Prediction of RNA Secondary Structure

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    Ribonucleic acid, RNA, is an essential type of molecule for all known forms of life. It is a nucleic acid, like DNA. However, where DNA appears as two complementary strands that join and twist into a double helix structure, RNA has only a single strand. This strand can fold upon itself, pairing complementary bases. The resulting set of base pairs is the RNA secondary structure, also known as folding. It is typical that a prediction algorithm gives a large number of optimal or near-optimal foldings for an RNA sequence. Only in the simplest cases it is possible to manually go through all of these foldings, and in hard cases it is infeasible to even generate the full set of optimal foldings. In fact, we observe that the number of optimal foldings may be exponential in the sequence length, and that some naturally occurring RNA sequences of 2000–3000 bases in length have well over 10^100 optimal foldings, under the model of maximizing the number of base pairs. To help analyze the full set of optimal foldings, we apply the concept of safe and complete algorithms. In the presence of multiple optimal solutions, any partial solution that appears in all optimal solutions is called a safe part, and a safe and complete algorithm finds all of the safe parts. We show a trivial safe and complete algorithm that computes safety by going through the full set of optimal foldings. However, this algorithm is only practical for short RNA sequences that do not have too many optimal foldings. In order to analyze the harder RNA sequences, we develop and implement a novel polynomial-time safe and complete algorithm for RNA secondary structure prediction, using the model of maximizing base pairs. Using the dynamic programming approach, this new algorithm can compute how often each base pair and unpaired base appears in the full set of optimal foldings without having to produce the actual foldings. Our experimental evaluation shows that the safe parts of a folding are more likely to be biologically correct than the non-safe parts. We observe this both by using our implementation of the efficient safe and complete algorithm and by combining an existing predictor program with the trivial algorithm. As this existing predictor uses a modern minimum free energy model for predicting the RNA foldings, tests using this combination show that safety is a useful property, even beyond the simple maximum pairs model in our implementation

    Asymptotics for relative frequency when population is driven by arbitrary evolution

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    Strongly consistent estimates are shown, via relative frequency, for the probability of "white balls" inside a dichotomous urn when such a probability is an arbitrary continuous time dependent function over a bounded time interval. The asymptotic behaviour of relative frequency is studied in a nonstationary context using a Riemann-Dini type theorem for SLLN of random variables with arbitrarily different expectations; furthermore the theoretical results concerning the SLLN can be applied for estimating the mean function of unknown form of a general nonstationary process.Comment: 29 page

    Information-Based Physics: An Observer-Centric Foundation

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    It is generally believed that physical laws, reflecting an inherent order in the universe, are ordained by nature. However, in modern physics the observer plays a central role raising questions about how an observer-centric physics can result in laws apparently worthy of a universal nature-centric physics. Over the last decade, we have found that the consistent apt quantification of algebraic and order-theoretic structures results in calculi that possess constraint equations taking the form of what are often considered to be physical laws. I review recent derivations of the formal relations among relevant variables central to special relativity, probability theory and quantum mechanics in this context by considering a problem where two observers form consistent descriptions of and make optimal inferences about a free particle that simply influences them. I show that this approach to describing such a particle based only on available information leads to the mathematics of relativistic quantum mechanics as well as a description of a free particle that reproduces many of the basic properties of a fermion. The result is an approach to foundational physics where laws derive from both consistent descriptions and optimal information-based inferences made by embedded observers.Comment: To be published in Contemporary Physics. The manuscript consists of 43 pages and 9 Figure
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