Random overlap structures: properties and applications to spin glasses

Random overlap structures (ROSt’s) are random elements on the space of probability measures on the unit ball of a Hilbert space, where two measures are identified if they differ by an isometry. In spin glasses, they arise as natural limits of Gibbs measures under the appropriate algebra of functions. We prove that the so called ‘cavity mapping’ on the space of ROSt’s is continuous, leading to a proof of the stochastic stability conjecture for the limiting Gibbs measures of a large class of spin glass models. Similar arguments yield the proofs of a number of other properties of ROSt’s that may be useful in future attempts at proving the ultrametricity conjecture. Lastly, assuming that the ultrametricity conjecture holds, the setup yields a constructive proof of the Parisi formula for the free energy of the Sherrington–Kirkpatrick model by making rigorous a heuristic of Aizenman, Sims and Starr.     

Approximate Ultrametricity for Random Measures and Applications to Spin Glasses

In this documentname, we introduce a notion called “approximate ultrametricity,” which encapsulates the phenomenology of a sequence of random probability measures having supports that behave like ultrametric spaces insofar as they decompose into nested balls. We provide a sufficient condition for a sequence of random probability measures on the unit ball of an infinite‐dimensional separable Hilbert space to admit such a decomposition, whose elements we call clusters. We also characterize the laws of the measures of the clusters by showing that they converge in law to the weights of a Ruelle probability cascade. These results apply to a large class of classical models in mean field spin glasses. We illustrate the notion of approximate ultrametricity by proving a conjecture of Talagrand regarding mixed p‐spin glasses that is known to imply a prediction of Dotsenko‐Franz‐Mézard. © 2017 Wiley Periodicals, Inc.     

Ultrametricity indices for the Euclidean and Boolean hypercubes

Motivated by Murtagh’s experimental observation that sparse random samples of the hypercube become more and more ultrametric as the dimension increases, we consider a strict version of his ultrametricity coefficient, an index derived from Rammal’s degree of ultrametricity, and a topological ultrametricity index. First, we prove that the three ultrametricity indices converge in probability to one as dimension increases, if the sample size remains fixed. This is done for uniformly and normally distributed samples in the Euclidean hypercube, and for uniformly distributed samples in F₂ ^N with Hamming distance, as well as for very general probability distributions. Further, this holds true for random categorial data in complete disjunctive form. A second result is that the ultrametricity indices vanish in the limit for the full hypercube F₂ ^N as dimensionN increases,whereby Murtagh’s ultrametricity index is largest, and the topological ultrametricity index smallest, if N is large.     

Ultrametric model of mind,II: Application to text content analysis

In a companion paper, Murtagh (2012), we discussed how Matte Blanco’s work linked the unrepressed unconscious (in the human) to symmetric logic and thought processes. We showed how ultrametric topology provides a most useful representational and computational framework for this. Now we look at the extent to which we can find ultrametricity in text. We use coherent and meaningful collections of nearly 1000 texts to show how we can measure inherent ultrametricity. On the basis of our findings we hypothesize that inherent ultrametricity is a basis for further exploring unconscious thought processes.     

On stochastic generation of ultrametrics in high-dimensional Euclidean spaces

We present a proof of the theorem which states that a matrix of Euclidean distances on a set of specially distributed random points in the n-dimensional Euclidean space R ⁿ converges in probability to an ultrametric matrix as n → ∞. Values of the elements of an ultrametric distance matrix are completely determined by variances of coordinates of random points. Also we present a probabilistic algorithm for generation of finite ultrametric structures of any topology in high-dimensional Euclidean space. Validity of the algorithm is demonstrated by explicit calculations of distance matrices and ultrametricity indexes for various dimensions n.     

Construction of pure states in mean field models for spin glasses

If a mean field model for spin glasses is generic in the sense that it satisfies the extended Ghirlanda–Guerra identities, and if the law of the overlaps has a point mass at the largest point q* of its support, we prove that one can decompose the configuration space into a sequence of sets (A _k ) such that, generically, the overlap of two configurations is equal to q* if and only if they belong to the same set A _k . For the study of the overlaps each set A _k can be replaced by a single point. Combining this with a recent result of Panchenko (A connection between Ghirlanda–Guerra identities and ultrametricity. Ann Probab (2008, to appear)) this proves that if the overlaps take only finitely many values, ultrametricity occurs. We give an elementary, self-contained proof of this result based on simple inequalities and an averaging argument.     

Storage and retrieval of ultrametric patterns in a network of CA1 neurons of the hippocampus

We explore the possibility of storage and retrieval of ultrametrically organized patterns in hippocampus, the part of the brain devoted to the memory processes. The ultrametric structure has been chosen for having a good representation of the categories of memory. The storage and retrieval process is the one typical of the hippocampus and it is based on the dynamic of the CA1 neurons under the input from the neurons of the Enthorinal cortex and the Ca3 system. We explore if this real system of neurons exhibits the property of associative memory introduced since a long time in the artificial neural networks. We study how the performance is dependent on the deviation of the system of patterns from ultrametricity. The evolution of the system is simulated by means of a parallel computer and the statistics of storage and retrieval is investigated.     

基于距离相关系数的分层聚类法

随着大数据时代的到来，各个领域涌现出海量数据且结构复杂.如变量的维数不同、尺度不同等.而现实中变量之间往往存在着不确定关系，经典的Pearson相关系数仅能反映两个同维变量间的线性相关关系，不足以完全刻画变量间的相关关系.2007年Szekely等提出的距离相关系数则能描述不同维数变量间的非线性关系.为了探索变量之间的内在信息，本文基于距离相关系数提出了最大距离相关系数法对变量聚类，且有超度量性和空间收缩性.为充分发挥距离相关系数的优势，对上述方法改进得到类整体距离相关系数法.该方法在刻画两类间相似性时，将每类中的所有变量合并成一个整体，再计算这两个不同维数的整体间的距离相关系数.最后，将类整体距离相关系数法应用到几个实际问题中，验证了算法的有效性.     

On L2-Dissipativity of a Linearized Explicit Finite-Difference Scheme with Quasi-Gasdynamic Regularization for the Barotropic Gas Dynamics System of Equations

Doklady Mathematics - We study an explicit two-level symmetric (in space) finite-difference scheme for the multidimensional barotropic gas dynamics system of equations with quasi-gasdynamic...     

An ultrametricity condition for pretangent spaces

A criterion for the ultrametricity of pretangent spaces to general metric spaces is obtained.     

On the dynamical properties of an elliptical–oval billiard with static boundary

Some dynamical properties for a classical particle confined inside a closed region with an elliptical–oval-like shape are studied. The dynamics of the model is made by using a two-dimensional nonlinear mapping. The phase space of the system is of mixed kind and we have found the condition that breaks the invariant spanning curves in the phase space. We have discussed also some statistical properties of the phase space and obtained the behaviour of the positive Lyapunov exponent.     

Ultrametricity and metric betweenness in tangent spaces to metric spaces

The paper deals with pretangent spaces to general metric spaces. An ultrametricity criterion for pretangent spaces is found and it is closely related to the metric betweenness in the pretangent spaces.     

Viability Theorem for Deterministic Mean Field Type Control Systems

A mean field type control system is a dynamical system in the Wasserstein space describing an evolution of a large population of agents with mean-field interaction under a control of a unique decision maker. We develop the viability theorem for the mean field type control system. To this end we introduce a set of tangent elements to the given set of probabilities. Each tangent element is a distribution on the tangent bundle of the phase space. The viability theorem for mean field type control systems is formulated in the classical way: the given set of probabilities on phase space is viable if and only if the set of tangent distributions intersects with the set of distributions feasible by virtue of dynamics.     

Predicting high-codimension critical transitions in dynamical systems using active learning

Complex dynamical systems, from those appearing in physiology and ecology to Earth system modelling, often experience critical transitions in their behaviour due to potentially minute changes in their parameters. While the focus of much recent work, predicting such bifurcations is still notoriously difficult. We propose an active learning approach to the classification of parameter space of dynamical systems for which the codimension of bifurcations is high. Using elementary notions regarding the dynamics, in combination with the nearest-neighbour algorithm and Conley index theory to classify the dynamics at a predefined scale, we are able to predict with high accuracy the boundaries between regions in parameter space that produce critical transitions.     

Study of degenerate evolution equations with memory by operator semigroup methods

We reduce the problem with some history prescribed for an integrodifferential equation in a Banach space including memory effect to the Cauchy problem for some evolution system with a constant operator in a larger space that possesses a resolvent (C₀)-semigroup. This enables us to state conditions for the existence of a unique classical solution to the original problem. We use the results to study the unique solvability of problems with history prescribed for degenerate linear evolution equations with memory in Banach spaces. We show that the initial-boundary value problem for the linearized integrodifferential Oskolkov system describing the dynamics of Kelvin–Voigt fluids in linear approximation belongs to this class of problems.     

An entropic gradient structure for quasi-steady-state approximations of chemical reactions

Passing to the limit of an infinite reaction rate in a slow-fast system of chemical reactions provides a quasi-steady state approximation (QSSA) of these systems. In case of reactions with detailed balance condition, this approximation includes a dimension reduction to a smaller state space. We show that the limit dynamics carry an entropic gradient structure on this smaller space. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Computational method for phase space transport with applications to lobe dynamics and rate of escape

Lobe dynamics and escape from a potential well are general frameworks introduced to study phase space transport in chaotic dynamical systems.While the former approach studies how regions of phase space get transported by reducing the flow to a two-dimensional map, the latter approach studies the phase space structures that lead to critical events by crossing certain barriers. Lobe dynamics describes global transport in terms of lobes, parcels of phase space bounded by stable and unstable invariant manifolds associated to hyperbolic fixed points of the system. Escape from a potential well describes how the critical events occur and quantifies the rate of escape using the flux across the barriers. Both of these frameworks require computation of curves, intersection points, and the area bounded by the curves. We present a theory for classification of intersection points to compute the area bounded between the segments of the curves. This involves the partition of the intersection points into equivalence classes to apply the discrete form of Green’s theorem. We present numerical implementation of the theory, and an alternate method for curves with nontransverse intersections is also presented along with a method to insert points in the curve for densification.     

Evolving chaos: Identifying new attractors of the generalised Lorenz family

In a recent paper, we presented an intelligent evolutionary search technique through genetic programming (GP) for finding new analytical expressions of nonlinear dynamical systems, similar to the classical Lorenz attractor's which also exhibit chaotic behaviour in the phase space. In this paper, we extend our previous finding to explore yet another gallery of new chaotic attractors which are derived from the original Lorenz system of equations. Compared to the previous exploration with sinusoidal type transcendental nonlinearity, here we focus on only cross-product and higher-power type nonlinearities in the three state equations. We here report over 150 different structures of chaotic attractors along with their one set of parameter values, phase space dynamics and the Largest Lyapunov Exponents (LLE). The expressions of these new Lorenz-like nonlinear dynamical systems have been automatically evolved through multi-gene genetic programming (MGGP). In the past two decades, there have been many claims of designing new chaotic attractors as an incremental extension of the Lorenz family. We provide here a large family of chaotic systems whose structure closely resemble the original Lorenz system but with drastically different phase space dynamics. This advances the state of the art knowledge of discovering new chaotic systems which can find application in many real-world problems. This work may also find its archival value in future in the domain of new chaotic system discovery.     

Existence and uniqueness of solutions for Fokker–Planck equations on Hilbert spaces

We consider a stochastic differential equation in a Hilbert space with time-dependent coefficients for which no general existence and uniqueness results are known. We prove, under suitable assumptions, the existence and uniqueness of a measure valued solution, for the corresponding Fokker–Planck equation. In particular, we verify the Chapman–Kolmogorov equations and get an evolution system of transition probabilities for the stochastic dynamics informally given by the stochastic differential equation.     

On the dynamics of equations with infinite delay

We consider a system of ordinary differential equations with infinite delay. We study large time dynamics in the phase space of functions with an exponentially decaying weight. The existence of an exponential attractor is proved under the abstract assumption that the right-hand side is Lipschitz continuous. The dimension of the attractor is explicitly estimated. Research supported by the project LC06052 of the Czech Ministry of Education.