Quantum computing? How about kwantumberekening?

Last week, Gerhard Woithe, who just joined the Group as an MSc student, started a project to translate the Wikipedia page for “Quantum computing” to Afrikaans. The page (still in progress) can be found at https://af.wikipedia.org/wiki/Kwantumberekening.

In the process of doing so, we have, however, found that in many cases, there are no existing Afrikaans terms for the (in many cases, relatively recent) jargon involved in the field of quantum computing. The first and most obvious untranslated term that jumped out at us was the term “qubit”, which, as everyone knows, is a portmanteau of the words “quantum” and “bit”. Well, the obvious analogue in Afrikaans is to chop and glue together the equivalent words “kwantum” and “bis”, to form the neologism “kwabis”, and so this is exactly what we did.

Stellenbosch University’s Department of Physics is essentially right across the road from the main offices of the Woordebook van die Afrikaanse Taal (WAT), and so after a few emails and with the keen assistance of the people at the WAT, the term “kwabis” has now been added as a lemma to the online version of the dictionary, subject to official approval.

It was brought to our attention by Alet Cloete at the WAT that the word had actually been used at least once before in the current sense in a 2005 review article published in the “Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie” (see https://www.researchgate.net/publication/307846633_Kwantumberekening). We think that the fact that the term “kwabis” has now been independently invented at least twice is an indication that it is the right word for the job.

Interestingly, the first documented use of the word itself is amazingly obscure – in a 1990 “poskantoorwoordeboek”, a post office dictionary, this term is given as the Afrikaans translation of the term “nibble” (see https://www.prolingua.org.za/dokumente/Poskantoorwoordeboek.pdf)

This translation effort is an ongoing project, and as we move on to more articles and as new untranslated terms come up, we will be keeping in close contact with the people of the WAT in order to have them added to the dictionary! Interest in creating and maintaining scientific terminology in Afrikaans has dwindled over the past few years. So we hope to, via this project, play at least a small part in stimulating interest in the (multilingual) lexicography of quantum computing. Additionally, we hope that this project perhaps inspires more people to be creative with language and translate technical articles into their home languages, thereby making specialised fields more easily accessible to people all over the world.

Please contact us if you are interested in making a contribution or if you have any suggestions for us.


The “kwabis”entry in the Woordebook van die Afrikaanse Taal (WAT).

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Four new preprints

What a day: 4 preprints in the arXiv!

Congratulations to Shivani Pillay, Ian David, Rowan Pellow-Jarman and Shane McFarthing for submitting their first preprints to the arXiv:

Hybrid Genetic Optimisation for Quantum Feature Map Design R Pellow-Jarman, A Pillay, I Sinayskiy, F Petruccione

Digital Simulation of Single Qubit Markovian Open Quantum Systems: A Tutorial , IJ David, I Sinayskiy, F Petruccione

A Multi-Class SWAP-Test Classifier, SM Pillay, I Sinayskiy, E Jembere, F Petruccione

Classical Ensembles of Single-Qubit Quantum Variational Circuits for Classification, S McFarthing, A Pillay, I Sinayskiy, F Petruccione



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Quantum @SUN welcomes Prof Uwe Jaekel

Prof Uwe Jaekel (Hochshule Koblenz, University of Applied Sciences) is visiting Stellenbosch University from 31 January to 5 February 2023.

Prof Jaekel is one of the speakers at the 2023 CHPC-NITheCS Summer School on Theoretical and Computational Sciences.

On Friday, 3 February, he will deliver a Colloquium on the topic ‘Solving nonlinear classification problems with a complex valued almost linear perceptron”.

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Quantum Unconference

It was great to have some of my UKZN students visiting in Stellenbosch and join the local team.

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Quantum tunnelling in the context of SARS‐CoV‐2 infection

The latest paper with Betony Adams, Ilya Sinayskiy and Rienk van Grondelle was published in Scientific Reports.

The SARS-CoV-2 spike protein facilitates host cell invasion by binding with cell membrane embedded ACE2 receptors.

A simplified illustration of vibration assisted tunnelling in the context of SARS-CoV-2 infection. The spike protein vibrational spectrum matches the energy of transition for an electron in the ACE2 receptor, facilitating electron transfer and the activation of the receptor.


The SARS‐CoV‐2 pandemic has added new urgency to the study of viral mechanisms of infection. But while vaccines offer a measure of protection against this specific outbreak, a new era of pandemics has been predicted. In addition to this, COVID‐19 has drawn attention to post‐viral syndromes and the healthcare burden they entail. It seems integral that knowledge of viral mechanisms is increased through as wide a research field as possible. To this end we propose that quantum biology might offer essential new insights into the problem, especially with regards to the important first step of virus‐ host invasion. Research in quantum biology often centres around energy or charge transfer. While this is predominantly in the context of photosynthesis there has also been some suggestion that cellular receptors such as olfactory or neural receptors might employ vibration assisted electron tunnelling to augment the lock‐and‐key mechanism. Quantum tunnelling has also been observed in enzyme function. Enzymes are implicated in the invasion of host cells by the SARS‐CoV‐2 virus. Receptors such as olfactory receptors also appear to be disrupted by COVID‐19. Building on these observations we investigate the evidence that quantum tunnelling might be important in the context of infection with SARS‐CoV‐2. We illustrate this with a simple model relating the vibronic mode of, for example, a viral spike protein to the likelihood of charge transfer in an idealised receptor. Our results show a distinct parameter regime in which the vibronic mode of the spike protein enhances electron transfer. With this in mind, novel therapeutics to prevent SARS‐CoV‐2 transmission could potentially be identified by their vibrational spectra.

Adams, B., Sinayskiy, I., van Grondelle, R. et al. Quantum tunnelling in the context of SARS-CoV-2 infection. Sci Rep 12, 16929 (2022).


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Dr Graeme Pleasance joins Quantum@SUN

We are very happy to welcome Graeme Pleasance as a PostDoc at Stellenbosch University. Graeme joined us on Monday 9 September 2022.

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Machine learning for excitation energy transfer dynamics

The latest paper with Kimara Naicker and Ilya Sinayskiy was just published in Physical Review Research.

Abstract: A wellknown approach to describe the dynamics of an open quantum system is to compute the master equation evolving the reduced density matrix of the system. This approach plays an important role in describing excitation transfer through photosynthetic light harvesting complexes (LHCs). The hierarchical equations of motion (HEOM) was adapted by Ishizaki and Fleming [J. Chem. Phys.130, 234111 (2009)] to simulate open quantum dynamics in the biological regime. We generate a set of time-dependent observables that depict the coherent propagation of electronic excitations through the LHCs by solving the HEOM. The computationally intractable problem here is addressed using classical machine learning (ML). The ML architecture constructed here is of model character and it is used to solve the inverse problem for open quantum systems within the HEOM approach. The objective is to determine whether a trained ML model can perform Hamiltonian tomography by using the time dependence of the observables as inputs. We demonstrate the capability of convolutional neural networks to tackle this research problem. The models developed here can predict Hamiltonian parameters such as excited state energies and inter-site couplings of a system up to 99.28% accuracy.

Reference: Kimara Naicker, Ilya Sinayskiy, and Francesco Petruccione,  Machine learning for excitation energy transfer dynamics, Phys. Rev. Research 4, 033175 – Published 6 September 2022

The pdf can be downloaded from here


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Compact quantum kernel-based binary classifier

My first paper with Stellenbosch University affiliation was published in Quantum Science and Technology.

Abstract: Quantum computing opens exciting opportunities for kernel-based machine learning methods, which have broad applications in data analysis. Recent works show that quantum computers can efficiently construct a model of a classifier by engineering the quantum interference effect to carry out the kernel evaluation in parallel. For practical applications of these quantum machine learning methods, an important issue is to minimize the size of quantum circuits. We present the simplest quantum circuit for constructing a kernel-based binary classifier. This is achieved by generalizing the interference circuit to encode data labels in the relative phases of the quantum state and by introducing compact amplitude encoding, which encodes two training data vectors into one quantum register. When compared to the simplest known quantum binary classifier, the number of qubits is reduced by two and the number of steps is reduced linearly with respect to the number of training data. The two-qubit measurement with post-selection required in the previous method is simplified to single-qubit measurement. Furthermore, the final quantum state has a smaller amount of entanglement than that of the previous method, which advocates the cost-effectiveness of our method. Our design also provides a straightforward way to handle an imbalanced data set, which is often encountered in many machine learning problems.

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Measure of invertible dynamical maps under convex combinations of noninvertible dynamical maps

The latest paper with Vinayak Jagadish and R. Srikanth was just published in Physical Review A.

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Prof Francesco Petruccione joined SU

Prof Francesco Petruccione joined Stellenbosch University on 1 May 2022.

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