Markus Bursch

@markusbursch.bsky.social

Computational Chemist at FACCTs

Thorsten Gressling will give a presentation on the combination of #ParamusAI and #ORCA for "𝘈𝘶𝘵𝘰𝘮𝘢𝘵𝘦𝘥 𝘙𝘦𝘢𝘤𝘵𝘪𝘰𝘯 𝘔𝘦𝘤𝘩𝘢𝘯𝘪𝘴𝘮 𝘋𝘪𝘴𝘤𝘰𝘷𝘦𝘳𝘺 𝘸𝘪𝘵𝘩 𝘖𝘙𝘊𝘈 𝘢𝘯𝘥 𝘈𝘐 𝘈𝘨𝘦𝘯𝘵𝘴" at the ACS Spring in Atlanta. Check out NEB-TS in our tutorial: www.faccts.de/docs/orca/6.... #FACCTs #QuantumChem #CompChem #AI #ACS2026

Finding Transition States with NEB-TS - ORCA 6.1 TUTORIALS

faccts.de

Dear ORCA community, it took a while, but now the ORCA 6.0 article is out! It serves as generic reference for ORCA 6.x. However, if you are serious about supporting our efforts, please take note of the suggested citations at the end of each ORCA run. wires.onlinelibrary.wiley.com/doi/10.1002/...

Software Update: The ORCA Program System—Version 6.0

This article describes the philosophy behind- and new features in the ORCA quantum chemistry program suite, version 6.0.

wires.onlinelibrary.wiley.com

The accessibility of state-of-the-art quantum chemistry is a core aspect of ORCA. We are therefore particularly proud that ORCA (@FACCTs & @orca-qc-official.bsky.social) is being used in such innovative projects as El Agente. Check it out! #ORCAqc #CompChem #LLM #QuantumChem #ChemSky

Acceleration Consortium@accelerationc.bsky.social · last yr.

👋 🤖 Meet El Agente–an autonomous AI for performing computational chemistry, made by the Matter Lab @uoft.bsky.social. This #LLM-powered multi-agent system making computational chemistry more accessible will soon be available worldwide. Sign up 4 the launch: acceleration.utoronto.ca/news/meet-el...

This paper is the start of something big - a new way to use Multipoles in electronic structure calculations. We are extremely excited and proud that this is out now. pubs.acs.org/doi/10.1021/...

The “Bubblepole” (BUPO) Method for Linear-Scaling Coulomb Matrix Construction with or without Density Fitting

In this work, we describe the development of a new algorithm for the computation of Coulomb-type matrices using the well-known resolution of the identity (RI) or density fitting (DF) approximation. The method is linear-scaling with respect to system size and computationally highly efficient. For small molecules, it performs almost as well as the Split-RI-J algorithm (which might be the most efficient RI-J implementation to date), while outperforming it for larger systems with about 300 or more atoms. The method achieves linear scaling through multipole approximations and a hierarchical treatment of multipoles. However, unlike in the fast multipole method (FMM), the algorithm does not use a hierarchical boxing algorithm. Rather, close-lying objects like auxiliary basis shells and basis set shell pairs are grouped together in spheres that enclose the set of objects completely, which includes a new definition of the shell-pair extent that defines a real-space radius outside of which a given shell pair can be safely assumed to be negligible. We refer to these spheres as “bubbles” and therefore refer to the algorithm as the “Bubblepole” (BUPO) algorithm, with the acronym being RI-BUPO-J. The bubbles are constructed in a way to contain a nearly constant number of objects such that a very even workload arises. The hierarchical bubble structure adapts itself to the molecular topology and geometry. For any target object (shell pair or auxiliary shell), one might envision that the bubbles “carve” out what might be referred to as a “far-field surface”. Using the default settings determined in this work, we demonstrate that the algorithm reaches submicro-Eh and even nano-Eh accuracy in the total Coulomb energy for systems as large as 700 atoms and 7000 basis functions. The largest calculations performed (the crambin protein solvated by 500 explicit water molecules in a triple-ζ basis) featured more than 2000 atoms and more than 33,000 basis functions.

pubs.acs.org

The ORCA team is looking for a postdoctoral fellow or Ph.D. student to work on XTB methodology jointly with the group of Prof. Stefan Grimme (University of Bonn).

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