8,962 research outputs found

    Formalizing Mathematical Knowledge as a Biform Theory Graph: A Case Study

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    A biform theory is a combination of an axiomatic theory and an algorithmic theory that supports the integration of reasoning and computation. These are ideal for formalizing algorithms that manipulate mathematical expressions. A theory graph is a network of theories connected by meaning-preserving theory morphisms that map the formulas of one theory to the formulas of another theory. Theory graphs are in turn well suited for formalizing mathematical knowledge at the most convenient level of abstraction using the most convenient vocabulary. We are interested in the problem of whether a body of mathematical knowledge can be effectively formalized as a theory graph of biform theories. As a test case, we look at the graph of theories encoding natural number arithmetic. We used two different formalisms to do this, which we describe and compare. The first is realized in CTTuqe{\rm CTT}_{\rm uqe}, a version of Church's type theory with quotation and evaluation, and the second is realized in Agda, a dependently typed programming language.Comment: 43 pages; published without appendices in: H. Geuvers et al., eds, Intelligent Computer Mathematics (CICM 2017), Lecture Notes in Computer Science, Vol. 10383, pp. 9-24, Springer, 201

    Anomalous price impact and the critical nature of liquidity in financial markets

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    We propose a dynamical theory of market liquidity that predicts that the average supply/demand profile is V-shaped and {\it vanishes} around the current price. This result is generic, and only relies on mild assumptions about the order flow and on the fact that prices are (to a first approximation) diffusive. This naturally accounts for two striking stylized facts: first, large metaorders have to be fragmented in order to be digested by the liquidity funnel, leading to long-memory in the sign of the order flow. Second, the anomalously small local liquidity induces a breakdown of linear response and a diverging impact of small orders, explaining the "square-root" impact law, for which we provide additional empirical support. Finally, we test our arguments quantitatively using a numerical model of order flow based on the same minimal ingredients.Comment: 16 pages, 7 figure

    Autocorrelation of Random Matrix Polynomials

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    We calculate the autocorrelation functions (or shifted moments) of the characteristic polynomials of matrices drawn uniformly with respect to Haar measure from the groups U(N), O(2N) and USp(2N). In each case the result can be expressed in three equivalent forms: as a determinant sum (and hence in terms of symmetric polynomials), as a combinatorial sum, and as a multiple contour integral. These formulae are analogous to those previously obtained for the Gaussian ensembles of Random Matrix Theory, but in this case are identities for any size of matrix, rather than large-matrix asymptotic approximations. They also mirror exactly autocorrelation formulae conjectured to hold for L-functions in a companion paper. This then provides further evidence in support of the connection between Random Matrix Theory and the theory of L-functions

    A Bit-String Model for Biological Aging

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    We present a simple model for biological aging. We studied it through computer simulations and we have found this model to reflect some features of real populations.Comment: LaTeX file, 4 PS figures include

    Market impact and trading profile of large trading orders in stock markets

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    We empirically study the market impact of trading orders. We are specifically interested in large trading orders that are executed incrementally, which we call hidden orders. These are reconstructed based on information about market member codes using data from the Spanish Stock Market and the London Stock Exchange. We find that market impact is strongly concave, approximately increasing as the square root of order size. Furthermore, as a given order is executed, the impact grows in time according to a power-law; after the order is finished, it reverts to a level of about 0.5-0.7 of its value at its peak. We observe that hidden orders are executed at a rate that more or less matches trading in the overall market, except for small deviations at the beginning and end of the order.Comment: 9 pages, 7 figure

    Long-range memory model of trading activity and volatility

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    Earlier we proposed the stochastic point process model, which reproduces a variety of self-affine time series exhibiting power spectral density S(f) scaling as power of the frequency f and derived a stochastic differential equation with the same long range memory properties. Here we present a stochastic differential equation as a dynamical model of the observed memory in the financial time series. The continuous stochastic process reproduces the statistical properties of the trading activity and serves as a background model for the modeling waiting time, return and volatility. Empirically observed statistical properties: exponents of the power-law probability distributions and power spectral density of the long-range memory financial variables are reproduced with the same values of few model parameters.Comment: 12 pages, 5 figure

    Distribution of parallel vortices studied by spin-polarized neutron reflectivity and magnetization

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    We present the studies of non-uniformly distributed vortices in Nb/Al multilayers at applied field near parallel to film surface by using spin-polarized neutron reflectivity (SPNR) and DC magnetization measurements. We have observed peaks above the lower critical field, Hc1, in the M-H curves from the multilayers. Previous works with a model calculation of minimizing Gibbs free energy have suggested that the peaks could be ascribed to vortex line transitions for spatial commensuration in a thin film superconductor. In order to directly determine the distribution of vortices, we performed SPNR measurements on the multilayer and found that the distribution and density of vortices are different at ascending and descending fields. At ascending 2000 Oe which is just below the first peak in the M-H curve, SPNR shows that vortices are mostly localized near a middle line of the film meanwhile the vortices are distributed in broader region at the descending 2000 Oe. That is related to the observation of more vortices trapped at the descending field. As the applied field is sightly tilted (< 3.5degree), we observe another peak at a smaller field. The peak position is consistent with the parallel lower critical field (Hc1||). We discuss that the vortices run along the applied field below Hc1|| and rotate parallel to the surface at Hc1||.Comment: 17 pages, 9 figure

    Lower order terms in the full moment conjecture for the Riemann zeta function

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    We describe an algorithm for obtaining explicit expressions for lower terms for the conjectured full asymptotics of the moments of the Riemann zeta function, and give two distinct methods for obtaining numerical values of these coefficients. We also provide some numerical evidence in favour of the conjecture.Comment: 37 pages, 4 figure
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