** Daniele Coslovich**

Associate professor

Statistical Physics group

Charles Coulomb Laboratory

University of Montpellier

**Contact:**

Laboratoire Charles Coulomb

Université de Montpellier

Place Eugène Bataillon

34095 Montpellier (France)

Phone: +33 (0)4 67149306

daniele.coslovich(at)umontpellier.fr

## Research interests

My research interests concern the physics of **disordered states of matter**, with particular focus on the microscopic mechanisms of **glass formation** and on glass structure. I am also interested in modeling the peculiar phase behavior, structure and dynamics of **soft condensed matter**.

My work is based on the methods of **statistical physics** and on **computer simulations**. Over the years I developed a computational approach based on **reproducible research**, **high-performance computing** and on high-level **simulation frameworks** like atooms, which I develop.

### Recent papers and seminars

"**Assessing the structural heterogeneity of supercooled liquids through community inference**"

J. Paret, R. Jack, D. Coslovich, The Journal of Chemical Physics **152**, 144502 (2020)

"**A localization transition underlies the mode-coupling crossover of glasses**"

D. Coslovich, A. Ninarello, L. Berthier, SciPost Physics **7**, 077 (2019)

"**Dynamic and thermodynamic crossover scenarios in the Kob-Andersen mixture: Insights from multi-CPU and multi-GPU simulations**"

D. Coslovich, M. Ozawa, W. Kob, The European Physical Journal E **41**, 62 (2018)

"**Local order and crystallization of dense polydisperse hard spheres**"

D. Coslovich, M. Ozawa, L. Berthier, Journal of Physics: Condensed Matter **30**, 144004 (2018)

"**Statistical inference of structural communities in supercooled liquids**"

Laboratoire de Physiques de Solides, Université Paris-Sud, Paris (France), 2020

"**Structural communities**"

Meeting of the Simons collaboration "Cracking the glass problem", Royaumont (France), 2019

"**A new characteristic temperature for glassy dynamics**"

Viscous Liquids and the Glass Transition (XVI), Holbaek (Denmark), 2019

"**Towards a coherent picture of the mode-coupling glass crossover**"

The Physical Society of Japan 2019 Annual (74th) Meeting, Fukuoka (Japan), 2019

## Codes

**The codes below are available on my git repository**

I developed a python framework called atooms to perform computer simulations and analyze their results. It provides an expressive, high-level interface to the main objects of particle simulations.

#### Atooms

Atooms is a collection of python packages that provide a high-level, yet efficient framework to deal with particle-based simulations, such as molecular dynamics or Monte Carlo. It is composed by a base library and additional packages that implement complex simulation strategies or analysis tools.

Tutorial » Notebook » Public API »#### Parallel tempering

Atooms-pt is the first simulation package I built on top of the atooms framework. It implements a multi-GPU parallel tempering simulation and relies on RUMD, an efficient molecular dynamics code developed by Glass and Time at the University of Roskilde.

Tutorial »#### Postprocessing

The atooms-pp package provides python tools to compute static and dynamic correlation functions from particle-based simulation data.

Francesco Turci contributed a jupyter notebook showing how to compute static and dynamic correlations of a Lennard-Jones mixture using the postprocessing package.

Tutorial » Notebook »#### Transition path sampling

The atooms-tps package, developed in collaboration with Francesco Turci, provides a generic frontend to transition path sampling simulations, which allow to sample rare fluctuations in the trajectory space of a dynamical system.

#### TASEP

TASEP is a minimal and pedagogical implementation of a totally asymmetric exclusion process with atooms. Developed toghether with Luca Ciandrini

#### gridengine-goodies

The gridengine-goodies package provides a few command line scripts that enhance the usability of the gridengine scheduling system.

#### orgnb

A script to convert an org-mode document with python blocks to jupyter notebook. It relies on pypandoc and jupyter modules.

#### TCC wrap

TCC wrap is a little command line wrapper to the Topological Cluster Classification code developed by Paddy Royall and coworkers at the University of Bristol.

### Reproducible research and data

I use the zenodo data repository to store citeable datasets and workflow associated to my research papers, as well as code snapshots. Here are a few recent data sets of mine

- Dataset and workflow for "A localization transition underlies the mode-coupling crossover of glasses" arXiv:1811.03171 (2019)

- Dataset for "Dynamic and thermodynamic crossover scenarios in the Kob-Andersen mixture: Insights from multi-CPU and multi-GPU simulations" Eur. Phys. J. E 62, 41 (2018)

- Dataset for "Local order and crystallization of dense polydisperse hard spheres" J. Phys.: Condens. Matter 30, 144004 (2018)

I use a federated, self-hosted nextcloud server to share data and projects with colleagues

Share with me via Nextcloud

## Teaching

I am the

**teaching supervisor**of the 2nd year of Physics degree at the University of Montpellier

#### Useful links for students of "L2 physique"

- Informations concernant les examens à la Faculté des Sciences
- Catalogue des formation de la Licence en Physique
- Page moodle da la L2 physique

This year I am teaching:

#### HLPH101 Physique générale

- Introductory classical mechanics (exercices)

#### HLPH305 Thermodynamique 2

- Axiomatic formulation of thermodynamics
- Thermodynamic potentials and application to phase transitions
- Introduction to irreversible phenomena
- Microscopic interpretation of temperature, pressure, entropy

#### HLPH402 Modélisation et algorithmique

- Introduction to python
- Solution of linear differential equations and application to population dynamics models
- Random walks

#### HMPH308 Simulations atomistiques avancées

- Code optimization, vectorization
- Parallelization with OpenMP and MPI
- Neighbor lists and optimization strategies for molecular simulations
- Parallel molecular dynamics