Introduction to Entos - QM Simulation Software for PCs, HPC, and the Cloud


Instructor: Thomas Miller (Professor at Caltech and Entos co-founder) and Daniel Smith (Entos)

Time: Friday, April 10, 1:30PM-4:00PM

Location: Zoom session only

Prerequisites: Working knowledge of basic electronic structure methods for chemistry/materials; Basic Unix/Linux, Python, or Jupyter notebook skills; GitHub account.

This course provides an introduction to the Entos quantum chemistry software. Entos enables ab initio molecular dynamics calculations on molecular and condensed-phase chemical reactions and other processes, with particular focus on mean-field (i.e., DFT), quantum embedding methods, and physics-based machine-learning for electronic structure. The software is built to easily integrate with research workflows, allowing integration via simple text I/O, JSON output, and interactive Jupyter notebooks. The tutorial will be divided into two parts. The first part will focus on Entos basics, including how to run and integrate the software, and how to perform standard calculations (geometries, transition-state searches, implicit solvation, excited states, NMR and other spectroscopic properties). The second part will focus on unique methods that are available in Entos, including molecular-orbital-based machine learning, embedding methods, and advanced methods for optimization and conformational searches. The course will include demonstrations and a cloud-based interactive tutorial.

Course Materials

Presentation slides

The presentation slides are available as downloadable PDF files.

  • Introduction to Entos (Spring 2020): PDF


This course focuses on the following topics:

  • How and where to run Entos
  • Workflow Integration via JSON output
  • Using Entos in Jupyter
  • Entos Input language
  • Simple calculations:
    • geometry optimizations
    • transition-state searches
    • excited-states
    • NMR and spectroscopic properties
  • Advanced capabilities:
    • molecular-orbital-based machine learning
    • embedding methods
    • advanced methods for optimization and conformational searches

Note: To participate in any live demonstrations, please obtain a Github account. Additional information about Entos can be found at: