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v23.03.01

v23.03.01#

A Virtual Machine for Computational Materials Science

Installation instructions#

Get Quantum Mobile running on your computer in three simple steps:

  1. Download virtual machine image (6.1 GB)

  2. Install Virtual Box 6.1.6 or later (see https://www.virtualbox.org)

  3. Import virtual machine image into Virtualbox (16.2 GB) File => Import Appliance

Login credentials: username: max, password: moritz.
The default configuration of 2 cores and 1536 MB RAM can be adjusted in the VM settings.

Contact#

For issues encountered during installation, please first consult the FAQ page.

Please direct inquiries regarding Quantum Mobile to the Quantum Mobile support channel in the AiiDA Discourse

Changelog#

This build:

  • Upgrades Quantum Mobile to Ubuntu 20.04.4 LTS,

  • Introduces the mambaforge package management system. See Working with Conda for more details.

  • Upgrades AiiDA to version 2.2.2

  • Upgrades Quantum ESPRESSO to version 7.1.

  • Introduces aiida-pseudo, for pseudo-potential installs and management.

Build Process#

  • OS: MacOSX

  • Ansible: 2.10.17

  • Vagrant: 2.2.9

  • Virtualbox: 6.1.18r142142

  • Base VM Image: bento/ubuntu-20.04

Software Summary#

[Quantum Mobile]
version = 23.03.01
Operating System = Ubuntu 20.04.4 LTS
Login credentials = max / moritz

[Apt packages]
grace = 1:5.1.25-7build1
xcrysden = 1.6.2-3build1
default-jre = 2:1.11-72
rabbitmq-server = 3.8.2-0ubuntu1.4
postgresql-client = 12+214ubuntu0.1

[Conda 'aiida' environment]
aiida-core = 2.2.2-pyh1a96a4e_1@conda-forge
aiida-core.notebook = 2.2.2-pyh1a96a4e_1@conda-forge
aiida-pseudo = 1.0.0-pyhd8ed1ab_0@conda-forge
aiida-quantumespresso = 4.2.0-pyhd8ed1ab_0@conda-forge
ipykernel = 6.22.0-pyh210e3f2_0@conda-forge
jupyterlab = 3.5.3-pyhd8ed1ab_0@conda-forge
pip = 23.0.1-pyhd8ed1ab_0@conda-forge
python = 3.9.16-h2782a2a_0_cpython@conda-forge

[Conda 'abinit' environment]
abinit = 9.8.3-hd1b6b71_2@conda-forge
libxc = 4.3.4-h86c2bf4_2@conda-forge
mpich = 4.0.3-h846660c_100@conda-forge

[Conda 'bigdft' environment]
bigdft-suite = 1.9.3-mpi_mpich_py311h71b1498_0@conda-forge
libxc = 4.3.4-h86c2bf4_2@conda-forge
mpich = 4.0.3-h846660c_100@conda-forge

[Conda 'cp2k' environment]
cp2k = 9.1.0-py39_openmpi_0@conda-forge
libxc = 5.2.3-py311h9e0c992_2@conda-forge
openmpi = 4.1.2-hbfc84c5_0@conda-forge

[Conda 'fleur' environment]
fleur = 6.1-h005d346_1@conda-forge
libxc = 5.2.3-py311h9e0c992_2@conda-forge
openmpi = 4.1.2-hbfc84c5_0@conda-forge

[Conda 'wannier90' environment]
libxc = 5.2.3-py311h9e0c992_2@conda-forge
openmpi = 4.1.2-hbfc84c5_0@conda-forge
wannier90 = 3.1.0-hb97063f_2@conda-forge

[Conda 'nwchem' environment]
libxc = 5.2.3-py39hea1df8f_2@conda-forge
nwchem = 7.0.2-py39hea0d9f8_3@conda-forge
openmpi = 4.1.2-hbfc84c5_0@conda-forge

[Conda 'siesta' environment]
libxc = 5.2.3-py311h9e0c992_2@conda-forge
openmpi = 4.1.2-hbfc84c5_0@conda-forge
siesta = 4.1.5-nompi_hd3d39af_1002@conda-forge

[Conda 'yambo' environment]
libxc = 5.2.3-py311h9e0c992_2@conda-forge
openmpi = 4.1.2-hbfc84c5_0@conda-forge
yambo = 5.0.4-h6b7a505_1@conda-forge

[Conda 'visualise' environment]
cif2cell = 2.0.0a3-pyhd8ed1ab_0@conda-forge
gnuplot = 5.4.5-h142138f_1@conda-forge
jmol = 14.32.10-ha770c72_0@conda-forge
python = 3.9.16-h2782a2a_0_cpython@conda-forge
  
[Quantum ESPRESSO]
version = 7.1
components = pw.x, cp.x, pp.x, ph.x, neb.x, hp.x, wannier90.x, epw.x, tddfpt.x

[Pseudopotentials]
SSSP/PBE/efficiency/1.1 = /usr/local/share/pseudo_sssp_PBE_efficiency_1.1
v21.06.04   v23.04.03
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