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Anton Klimovsky

Publications and source records attributed to Anton Klimovsky.

15 recordsLinked to original sources
arXiv2024

Meeting times of Markov chains via singular value decomposition

We suggest a non-asymptotic matrix perturbation-theoretic approach to get sharp bounds on the expected meeting time of random walks on large (possibly random) graphs. We provide a formula for the expected meeting time in terms of the singular value decomposition of the diagonally killed generator of a pair of independent random walks, which we view as a perturbation of the generator. Employing a rank-one approximation of the diagonally killed generator as the proof of concept, we work out sharp bounds on the expected meeting time of simple random walks on sufficiently dense Erd\H{o}s-R\'enyi random graphs.

math.PR↗
arXiv2023

Continuum graph dynamics via population dynamics: well-posedness, duality and equilibria

This paper introduces graphemes for constructing and analyzing stochastic processes that describe the evolution of large dynamic graphs. Unlike graphons, which capture the static properties of dense graphs via exchangeability or subgraph densities, graphemes are capable of modeling the full space-time evolution of graphs. A grapheme is an equivalence class of triples: (Polish space, symmetric {0,1}-valued connection function, sampling probability measure). We focus on embeddings in ultrametric spaces, encoding the graph history and linking directly to population dynamics models. Graphemes utilize stronger equivalences (homeomorphism, isometry) than graphons. We construct grapheme-valued Markov processes as limits of finite graph evolutions, driven by Fleming-Viot, Dawson-Watanabe, and McKean-Vlasov analogues. We establish characterization via well-posed martingale problems, yielding strong Markov processes with the Feller property and continuous paths (diffusions). Duality relations involving coalescent processes are derived. We identify non-trivial equilibria, linked to classical distributions from population genetics. This framework extends [arXiv:1908.06241] by incorporating history, enabling rigorous analysis via martingale problems, and characterizing non-trivial long-term behavior.

math.PR↗
arXiv2023

The grapheme-valued Wright-Fisher diffusion with mutation

In [Athreya, den Hollander, Röllin; 2021, arXiv:1908.06241] models from population genetics were used to define stochastic dynamics in the space of graphons arising as continuum limits of dense graphs. In the present paper we exhibit an example of a simple neutral population genetics model for which this dynamics is a Markovian diffusion that can be characterised as the solution of a martingale problem. In particular, we consider a Markov chain in the space of finite graphs that resembles a Moran model with resampling and mutation. We encode the finite graphs as graphemes, which can be represented as a triple consisting of a vertex set, an adjacency matrix and a sampling measure. We equip the space of graphons with convergence of sample subgraph densities and show that the grapheme-valued Markov chain converges to a grapheme-valued diffusion as the number of vertices goes to infinity. We show that the grapheme-valued diffusion has a stationary distribution that is linked to the Poisson-Dirichlet distribution. In a companion paper [Greven, den Hollander, Klimovsky, Winter; 2023], we build up a general theory for obtaining grapheme-valued diffusions via genealogies of models in population genetics.

math.PR↗
arXiv2023

The phase diagram of the complex continuous random energy model: The weak correlation regime

We identify the fluctuations of the partition function of the continuous random energy model on a Galton-Watson tree in the so-called weak correlation regime. Namely, when the ``speed functions'', that describe the time-inhomogeneous variance, lie strictly below their concave hull and satisfy a certain weak regularity condition. We prove that the phase diagram coincides with the one of the random energy model. However, the fluctuations are different and depend on the slope of the covariance function at $0$ and the final time $t$.

math.PR↗
arXiv2018

Markovian dynamics of exchangeable arrays

We study Markov processes with values in the space of general two-dimensional arrays whose distribution is exchangeable. The results of this paper are inspired by the theory of exchangeable dynamical random graphs developed by H. Crane (2016, 2017).

math.PR↗
arXiv2017

The phase diagram of the complex branching Brownian motion energy model

We complete the analysis of the phase diagram of the complex branching Brownian motion energy model by studying Phases I, III and boundaries between all three phases (I-III) of this model. For the properly rescaled partition function, in Phase III and on the boundaries I/III and II/III, we prove a central limit theorem with a random variance. In Phase I and on the boundary I/II, we prove an a.s. and $L^1$ martingale convergence. All results are shown for any given correlation between the real and imaginary parts of the random energy.

math.PR↗
arXiv2017

The hierarchical Cannings process in random environment

In an earlier paper, we introduced and studied a system of hierarchically interacting measure-valued random processes which describes a large population of individuals carrying types and living in colonies labelled by the hierarchical group of order $N$. The individuals are subject to migration, resampling on all hierarchical scales simultaneously. Upon resampling, a random positive fraction of the population in a block of colonies inherits the type of a random single individual in that block, which is why we refer to our system as the hierarchical Cannings process. In the present paper, we study a version of the hierarchical Cannings process in random environment, namely, the resampling measures controlling the change of type of individuals in different blocks are chosen randomly with a given mean and are kept fixed in time (= the quenched setting). We give a necessary and sufficient condition under which a multi-type equilibrium is approached (= coexistence) as opposed to a mono-type equilibrium (= clustering). Moreover, in the hierarchical mean-field limit $N \to \infty$, with the help of a renormalization analysis, we obtain a full picture of the space-time scaling behaviour of block averages on all hierarchical scales simultaneously. We show that the $k$-block averages are distributed as the superposition of a Fleming-Viot diffusion with a deterministic volatility constant $d_k$ and a Cannings process with a random jump rate, both depending on $k$. In the random environment, $d_k$ turns out to be smaller than in the homogeneous environment of the same mean. We investigate how $d_k$ scales with $k$. This leads to five universality classes of cluster formation in the mono-type regime. We find that if clustering occurs, then the random environment slows down the growth of the clusters, i.e., enhances the diversity of types.

math.PR↗
arXiv2015

The glassy phase of the complex branching Brownian motion energy model

We identify the fluctuations of the partition function for a class of random energy models, where the energies are given by the positions of the particles of the complex-valued branching Brownian motion (BBM). Specifically, we provide the weak limit theorems for the partition function in the so-called "glassy phase" -- the regime of parameters, where the behaviour of the partition function is governed by the extrema of BBM. We allow for arbitrary correlations between the real and imaginary parts of the energies. This extends the recent result of Madaule, Rhodes and Vargas, where the uncorrelated case was treated. In particular, our result covers the case of the real-valued BBM energy model at complex temperatures.

math.PR↗
arXiv2014

Generalized Random Energy Model at Complex Temperatures

Motivated by the Lee--Yang approach to phase transitions, we study the partition function of the Generalized Random Energy Model (GREM) at complex inverse temperature $β$. We compute the limiting log-partition function and describe the fluctuations of the partition function. For the GREM with $d$ levels, in total, there are $\frac 12 (d+1)(d+2)$ phases, each of which can symbolically be encoded as $G^{d_1}F^{d_2}E^{d_3}$ with $d_1,d_2,d_3\in\mathbb{N}_0$ such that $d_1+d_2+d_3=d$. In phase $G^{d_1}F^{d_2}E^{d_3}$, the first $d_1$ levels (counting from the root of the GREM tree) are in the glassy phase (G), the next $d_2$ levels are dominated by fluctuations (F), and the last $d_3$ levels are dominated by the expectation (E). Only the phases of the form $G^{d_1}E^{d_3}$ intersect the real $β$ axis. We describe the limiting distribution of the zeros of the partition function in the complex $β$ plane (= Fisher zeros). It turns out that the complex zeros densely touch the positive real axis at $d$ points at which the GREM is known to undergo phase transitions. Our results confirm rigorously and considerably extend the replica-method predictions from the physics literature.

math.PR↗
arXiv2014

Renormalisation of hierarchically interacting Cannings processes

The present paper brings a new class of interacting jump processes into focus. We start from a single-colony $C^Λ$-process, which arises as the continuum-mass limit of a $Λ$-Cannings individual-based population model, where $Λ$ is a finite non-negative measure that describes the offspring mechanism. After that we introduce a system of hierarchically interacting $C^Λ$-processes, where the interaction comes from migration and reshuffling-resampling based on measures $(Λ_k)_{k}$ both acting in $k$-blocks of the hierarchical group. We refer to this system as the $C_N^{c,Λ}$-process. The dual process of the $C_N^{c,Λ}$-process is a spatial coalescent with multi-level block coalescence. For the above system we carry out a full renormalisation analysis in the hierarchical mean-field limit $N\to\infty$. Our main result is that, in the limit as $N\to\infty$, on each scale $k\in\mathbb{N}_0$ the $k$-block averages of the $C_N^{c,Λ}$-process converge to a random process that is a superposition of a $C^{Λ_k}$-process and a Fleming-Viot process, the latter with a volatility $d_k$ and with a drift of strength $c_k$ towards the limiting $(k+1)$-block average. It turns out that $d_k$ is a function of $c_l$ and $Λ_l$ for all $0\leq l<k$. Thus, it is through the volatility that the renormalisation manifests itself. We discuss the implications of the scaling of $d_k$ for the behaviour on large space-time scales of the $C_N^{c,Λ}$-process. We compare the outcome with what is known from the renormalisation analysis of hierarchically interacting Fleming-Viot diffusions, pointing out several new features. We obtain a new classification for when the process exhibits clustering, respectively, exhibits local coexistence. Finally, we show that for finite $N$ the same dichotomy between clustering and local coexistence holds as for $N\to\infty$.

math.PR↗
arXiv2012

Complex Random Energy Model: Zeros and Fluctuations

The partition function of the random energy model at inverse temperature $β$ is a sum of random exponentials $Z_N(β)=\sum_{k=1}^N \exp(β\sqrt{n} X_k)$, where $X_1,X_2,...$ are independent real standard normal random variables (= random energies), and $n=\log N$. We study the large $N$ limit of the partition function viewed as an analytic function of the complex variable $β$. We identify the asymptotic structure of complex zeros of the partition function confirming and extending predictions made in the theoretical physics literature. We prove limit theorems for the random partition function at complex $β$, both on the logarithmic scale and on the level of limiting distributions. Our results cover also the case of the sums of independent identically distributed random exponentials with any given correlations between the real and imaginary parts of the random exponent.

math.PR↗
arXiv2011

High-dimensional Gaussian fields with isotropic increments seen through spin glasses

We study the free energy of a particle in (arbitrary) high-dimensional Gaussian random potentials with isotropic increments. We prove a computable saddle-point variational representation in terms of a Parisi-type functional for the free energy in the infinite-dimensional limit. The proofs are based on the techniques developed in the course of the rigorous analysis of the Sherrington-Kirkpatrick model with vector spins.

math.PR↗
arXiv2009

The Aizenman-Sims-Starr and Guerra's schemes for the SK model with multidimensional spins

We prove upper and lower bounds on the free energy in the Sherrington-Kirkpatrick model with multidimensional (e.g., Heisenberg) spins in terms of the variational inequalities based on the corresponding Parisi functional. We employ the comparison scheme of Aizenman, Sims and Starr and the one of Guerra involving the generalised random energy model-inspired processes and Ruelle's probability cascades. For this purpose an abstract quenched large deviations principle of the Gaertner-Ellis type is obtained. Using the properties of Ruelle's probability cascades and the Bolthausen-Sznitman coalescent, we derive Talagrand's representation of the Guerra remainder term for our model. We study the properties of the multidimensional Parisi functional by establishing a link with a certain class of the non-linear partial differential equations. Solving a problem posed by Talagrand, we show the strict convexity of the local Parisi functional. We prove the Parisi formula for the local free energy in the case of the multidimensional Gaussian a priori distribution of spins using Talagrand's methodology of the a priori estimates.

math.PR↗
arXiv2008

Fluctuations of the partition function in the GREM with external field

We study Derrida's generalized random energy model in the presence of uniform external field. We compute the fluctuations of the ground state and of the partition function in the thermodynamic limit for all admissible values of parameters. We find that the fluctuations are described by a hierarchical structure which is obtained by a certain coarse-graining of the initial hierarchical structure of the GREM with external field. We provide an explicit formula for the free energy of the model. We also derive some large deviation results providing an expression for the free energy in a class of models with Gaussian Hamiltonians and external field. Finally, we prove that the coarse-grained parts of the system emerging in the thermodynamic limit tend to have a certain optimal magnetization, as prescribed by strength of external field and by parameters of the GREM.

math.PR↗