Conditional Intensity and Gibbsianness of Determinantal Point Processes

نویسندگان

  • Hans-Otto Georgii
  • Hyun Jae Yoo
چکیده

The Papangelou intensities of determinantal (or fermion) point processes are investigated. These exhibit a monotonicity property expressing the repulsive nature of the interaction, and satisfy a bound implying stochastic domination by a Poisson point process. We also show that determinantal point processes satisfy the so-called condition ( λ), which is a general form of Gibbsianness. Under a continuity assumption, the Gibbsian conditional probabilities can be identified explicitly.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Gibbsianness of Fermion Random Point Fields

We consider fermion (or determinantal) random point fields on Euclidean space R. Given a bounded, translation invariant, and positive definite integral operator J on L(R), we introduce a determinantal interaction for a system of particles moving on R as follows: the n points located at x1, · · · , xn ∈ R have the potential energy given by U (x1, · · · , xn) := − log det(j(xi − xj))1≤i,j≤n, wher...

متن کامل

A Variational Principle in the Dual Pair of Reproducing Kernel Hilbert Spaces and an Application

Given a positive definite, bounded linear operator A on the Hilbert space H0 := l(E), we consider a reproducing kernel Hilbert space H+ with a reproducing kernel A(x, y). Here E is any countable set and A(x, y), x, y ∈ E, is the representation of A w.r.t. the usual basis of H0. Imposing further conditions on the operator A, we also consider another reproducing kernel Hilbert space H − with a ke...

متن کامل

Structured Determinantal Point Processes

We present a novel probabilistic model for distributions over sets of structures— for example, sets of sequences, trees, or graphs. The critical characteristic of our model is a preference for diversity: sets containing dissimilar structures are more likely. Our model is a marriage of structured probabilistic models, like Markov random fields and context free grammars, with determinantal point ...

متن کامل

A ug 2 00 6 Complex determinantal processes and H 1 noise

For the plane, sphere, and hyperbolic plane we consider the canonical invariant determinantal point processes Z ρ with intensity ρdν, where ν is the corresponding invariant measure. We show that as ρ → ∞, after centering, these processes converge to invariant H 1 noise. More precisely, for all functions f ∈ H 1 (ν) ∩ L 1 (ν) the distribution of z∈Zρ f (z) − ρ π f dν converges to Gaussian with m...

متن کامل

Learning Determinantal Point Processes in Sublinear Time

We propose a new class of determinantal point processes (DPPs) which can be manipulated for inference and parameter learning in potentially sublinear time in the number of items. This class, based on a specific low-rank factorization of the marginal kernel, is particularly suited to a subclass of continuous DPPs and DPPs defined on exponentially many items. We apply this new class to modelling ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005