activity
20072015
most citedDistribution of Time-Averaged Observables for Weak Ergodicity Breaking

142 citations · 404 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.stat-mech2015★ 1 cited

Reply to the comment on "Non-Normalizable Densities in Strong Anomalous Diffusion: Beyond the Central Limit Theorem"

Adi Rebenshtok, Sergey Denisov, Peter Hänggi +1

We provide a reply to a comment by I. Goychuk arXiv:1501.06996 [cond-mat.stat-mech] (not under active consideration with Phys. Rev. Lett.) on our Letter A. Rebenshtok, S. Denisov,…

cond-mat.stat-mech2014★ 59 cited

Infinite densities for Lévy walks

Adi Rebenshtok, Sergey Denisov, Peter Hanggi +1

Motion of particles in many systems exhibits a mixture between periods of random diffusive like events and ballistic like motion. In many cases, such systems exhibit strong anomalo…

cond-mat.stat-mech2014★ 20 cited

Occupation times on a comb with ramified teeth

Adi Rebenshtok, Eli Barkai

We investigate occupation time statistics for random walks on a comb with ramified teeth. This is achieved through the relation between the occupation time and the first passage ti…

cond-mat.stat-mech2013★ 99 cited

Non-normalizable densities in strong anomalous diffusion: beyond the central limit theorem

A. Rebenshtok, S. Denisov, P. Hanggi +1

Strong anomalous diffusion, where with a nonlinear spectrum $ν(q) \neq \mbox{const}$, is wide spread and has been found in various nonlin…

cond-mat.stat-mech2008★ 83 cited

Weakly non-ergodic Statistical Physics

Adi Rebenshtok, Eli Barkai

We find a general formula for the distribution of time averaged observables for weakly non-ergodic systems. Such type of ergodicity breaking is known to describe certain systems wh…

cond-mat.stat-mech2007★ 142 cited

Distribution of Time-Averaged Observables for Weak Ergodicity Breaking

Adi Rebenshtok, Eli Barkai

We find a general formula for the distribution of time-averaged observables for systems modeled according to the sub-diffusive continuous time random walk. For Gaussian random walk…