Local Number Fluctuations in Hyperuniform and Nonhyperuniform Systems

Our systematic study of local number fluctuations in both hyperuniform and nonhyperuniform systems has revealed some intriguing behaviors and provides useful tools for further studies:

Popular Summary by Physical Review X:
“The emerging field of ‘hyperuniformity’ provides mathematical tools for classifying large ensembles of particles based on the degree to which density fluctuations are suppressed according to their first two moments (the expected value and the variance). Originally formulated to describe how atoms are positioned in crystals, quasicrystals, and amorphous solids, the framework is useful in many studies, from the distribution of prime numbers to photoreceptor cells in avian retina. Here, we stress the importance of characterizing the higher-order moments of any system, hyperuniform or not.

To more completely characterize density fluctuations, we carry out an extensive theoretical and computational study of higher-order moments and the corresponding probability distribution function of a large class of models across the first three space dimensions. These models describe both hyperuniform and nonhyperuniform systems, that is, those in which density fluctuations are greatly suppressed and those in which they are not. Remarkably, we discover that diverse systems—encompassing the majority of our models—can be described by ‘universal’ distribution functions.

Our work elucidates the fundamental importance of higher-order structural information to fully characterize density fluctuations in many-body systems across length scales and dimensions, and thus it has broad implications for condensed-matter physics, engineering, mathematics, and biology.”


A few more details:
We derived rigorous bounds on higher-moments of the number distributions, beyond the number variance, and we developed a robust Gaussian “distance” metric for number distributions. We inferred the presence of three- and higher-body correlations in some of our models by the behaviors of the higher-order moments. Moreover, we showed for models that decorrelate or correlate, as the space dimension increases, that fluctuations become increasingly Gaussian or non-Gaussian, respectively. Finally, we found a universal behavior at intermediate sizes of the observation windows in that the number distributions are well approximated by gamma distributions for all of our distinctly different models that obey a CLT. For our models, we thus found that the convergence to a CLT is slower for standard nonhyperuniform models and slowest for the ‘antihyperuniform’ model studied here.

Supplementary dataset:
We have published all results of our analysis on Zenodo:


Low-temperature statistical mechanics of the Quantizer problem

Following up on our finding of a universal hidden order in tessellations with the Quantizer energy functionals (where the cells minimize the second moment of the volume distribution) using Lloyd’s algorithm, we now compared these states with quenches from equilibrium states at finite temperature.

Upon sufficiently fast non-equilibrium cooling, the system adopts similar states as the effectively hyperuniform inherent structures found by Lloyd’s algorithm and prevents the ordering transition into a body-centered cubic ordered structure.


Hyperuniform and rigid stable matchings

With respect to the degree of order and disorder, a snapshot of the ideal gas with completely independent particle positions (in mathematics known as the realization of a Poisson point process) is the exact opposite of a lattice with a perfect short- and long-range order.

We have defined a stable matching between these two extremes and proved that the resulting pattern can locally be virtually indistinguishable from the ideal gas but at large scales it inherits two remarkable global properties of the lattice: hyperuniformity and number rigidity, as demonstrated in our supplementary video.

M. A. Klatt, G. Last, D. Yogeshwaran. Hyperuniform and rigid stable matchings. Random Struct Alg. 57:439–473 (2020)

In the stable matching, points of the lattice and the ideal gas prefer to be close to each other. Assuming that there are on average more points per unit area in the ideal gas than in the lattice, the matched points in the ideal gas form a new point process that inherits properties from both the lattice and the ideal gas.

In fact, if the mean number of points per unit area converge, the new point pattern becomes almost indistinguishable from the ideal gas in any finite observation window, while its large-scale density fluctuations remain anomalously suppressed similar to the lattice.

We prove that the resulting point process is hyperuniform and number rigidity also for a stable matching between a lattice and not only the ideal gas but a class of correlated point processes, known as determinantal point processes. For a one-sided matching in 1D, our proof applies to quite general point processes.

Our paper solves an open question from the seminal paper by Salvatore Torquato and Frank Stillinger that introduced the notion of hyperuniformity. Our matched point processes generalizes a 1D hyperuniform point process by Goldstein, Lebowitz, Speer.

You can easily match two arbitrary point patterns using my R-package: matchingpp


Geometric Functionals of Fractal Percolation

Fractal percolation exhibits a dramatic topological phase transition, changing abruptly
from a dust-like set to a system-spanning cluster. Where this transition occurs is unknown
and notoriously difficult to estimate. In continuum percolation, the percolation thresholds have been approximated well using Minkowski functionals. Motivated by the question of whether a similar approach is possible for fractal models, we introduce corresponding geometric functionals for the fractal percolation process.

M. A. Klatt and S. Winter. Geometric functionals of fractal percolation. Adv. Appl. Probab. 52:1085–1126 (2020)

We establish the existence of the limit functionals and obtain explicit formulas for them as well as for their finite approximations (in excellent agreement with simulation result). They provide new geometric insights into fractal percolation. For example, we provide a mathematically rigorous notion of fractal subdimensions that have been previously defined in physics as an approach to refined information about fractal sets beyond fractal dimension.

My code to simulate fractal percolation and to analyze our geometric functionals is freely available at GitHub.


Detecting structured sources in noisy images via Minkowski maps

Distinguishing a feature from background noise is often the key to discovering physical phenomena in spatial data for a wide range of applications. We show how the sensitivity of a null hypothesis test can be dramatically increased by additional geometric information without the need for any prior knowledge about potential sources.

M. A. Klatt and K. Mecke. Detecting structured sources in noisy images via Minkowski maps. EPL (Europhysics Letters) 128:60001-p1–8 (2019)

We present a morphometric analysis technique, based on Minkowski functionals, to quantify the shape of structural deviations in greyscale images. It identifies important features in noisy spatial data, especially for short observation times and low statistics.
Without assuming any prior knowledge about potential sources, the additional shape information can increase the sensitivity by 14 orders of magnitude compared to previous methods. Rejection rates can increase by an order of magnitude.

As a key ingredient to such a dramatic increase, we accurately describe the distribution of the homogeneous background noise in terms of the density of states for the area, perimeter, and Euler characteristic of random black-and-white images. Remarkably, the density of states can vary by 64 orders of magnitude. We apply our technique to data of the H.E.S.S. experiment.

The density of states and my code for Minkowski maps are freely available at GitHub.

All simulated data and parameters underlying our study are available at Zenodo.


Cloaking the underlying long-range order of randomly perturbed lattices

How can we cloak the Bragg peaks of a lattice with random perturbations and will traces of the underlying long-range order persist nevertheless? Our affirmative answer to both questions has been published as an Editors’ Suggestion:

M. A. Klatt, J. Kim, S. Torquato. Cloaking the underlying long-range order of randomly perturbed lattices. Phys. Rev. E 101, 032118-1–9 (2020)

The Editors of Physical Review E have suggested our paper as a Highlight:
“When a regular lattice is perturbed, traces of the original lattice usually remain visible as Bragg peaks in the diffraction pattern. The authors of this paper consider uniformly randomized lattices and show that fine-tuned distributions of perturbations can hide the Bragg peaks. Interestingly, as the strength of the perturbations increases, long-range order oscillates and Bragg peaks appear and disappear.”


Phoamtonics: Photonic band gaps of 3D foams

In our paper, published in PNAS, we show how to construct a foam-based photonic crystal with a substantial band gap using the famous Weaire-Phelan foam.

M. A. Klatt, P. J. Steinhardt, S. Torquato. Phoamtonic designs yield sizeable 3D photonic band gaps. Proc. Natl. Acad. Sci. U.S.A. 116:23480–23486 (2019)

A report by Steven Schultz about our study has been featured on the main webpage of Princeton University:


See also, the original post of the engineering department:

The Weaire-Phelan foam has the smallest surface area among all known tessellations with equal-volume cells. While it has only a slightly smaller surface area than the Kelvin foam. Its corresponding photonic network provides a distinctly larger band gap and a much smaller critical refractive index. To determine the latter, we have created a detailed map of gap sizes.

Among the promising prospects that phoamtonics offers for applications are multifunctional characteristics, the self-organization of large photonic networks, and a high degree of isotropy.

We published all data generated or analyzed for our phoamtonics study, including configurations, parameter files, raw output, and postprocessed data, in a Zenodo
( DOI: 10.5281/zenodo.3401635


Strength of bacterial adhesion on nanostructured surfaces quantified by substrate morphometry

In this paper, we combine physics, microbiology and mathematics to study how bacteria attach to nanostructured surfaces, and how topography of nanostructured substrates can directly quantify the adhesion.

C. Spengler, F. Nolle, J. Mischo, T. Faidt, S. Grandthyll, N. Thewes, P. Jung, M.
Koch, F. Müller, M. Bischoff, M. A. Klatt, K. Jacobs. Strength of bacterial adhesion on nanostructured surfaces quantified by substrate morphometry. Nanoscale 11:19713–19722 (2019)

Aiming for 3D-structured materials for or against bio-adhesion, we studied mechanisms by which the bacteria adhere to different types of materials. Our insights help, for example, to prevent adhesion of pathogens (like Staphylococcus aureus) before the bacteria can begin to grow a biofilm, which protects individual bacteria from attack by antibiotics.

We found that the measured forces with which the individual bacterial cells adhered to nanostructured surfaces decrease with an increasing size of these nanostructures. In fact, with our morphometric analysis based on Minkowski functionals, we found that the strength of the adhesion force can be predicted from measurements of the surface area that is accessible to the tethering proteins with which the bacteria adhere to the surface. More precisely, we found that the ratio of the experimentally measured adhesion forces at the rough surface compared to a smooth surface agrees with the fraction of surface area that is accessible to the tethering proteins, which are about 50 nm long.

There are press releases in English and German.


Keynote on a hidden order among disorder

It has been my great pleasure to open the 15th International Congress for Stereology and Image Analysis in Aarhus, Denmark, with my keynote on:

How to find a hidden order among disorder

where I gave an introduction and overview on hyperuniformity. The study of this anomalous suppression of density fluctuations on large length scales has shed light on a variety of seemingly unrelated fields, from the eyes of chicken to exotic many-particle ensembles and random matrices. The unique properties of hyperuniform amorphous materials (with a hidden order such that the system remains macroscopically uniform, despite not being crystalline) have recently led to intense research in physics, mathematics, material science, and biology. Aiming for an intuitive understanding of the rigorous mathematical definitions, I presented both basic concepts and recent examples.

I thank the organizers for a great conference in the last week of May 2019 with many stimulating discussions across disciplines.


Focus Session at the APS March Meeting 2019

It has been my great pleasure to organize together with Lisa Manning, Gregory Grason, and Gerd Schröder-Turk a GSOFT Focus Session at the APS March Meeting in Boston this year:

"Hyperuniformity and Optimal Tessellations: Structure, Formation and Properties"

After recent breakthroughs in the search for ordered optimal tessellations (for example, including Frank-Kasper phases in copolymer melts), now findings of the optimal properties of amorphous tessellations are emerging, e.g., in biological tissues.

At the same time, there have been intensive studies of amorphous systems with an anomalous suppression of density fluctuations on large length scales, known as hyperuniformity. This geometric concept qualitatively and quantitatively characterizes a hidden-order in amorphous states that allows for unique physical properties – combining those of crystalline and disordered phases. Thus it offers candidates for optimal amorphous tessellations of space.

The two invited speakers of our session on Thursday, March 7, were Jasna Brujic and Salvatore Torquato.