# From Digital Humanities to Quantum Humanities: Potentials and Applications

arXiv: https://arxiv.org/abs/2103.11825 · HTML: https://mlsanity.com/paper/2103.11825/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 111 references that are in the map.
- First posted on arXiv 17 Mar 2021.

## Builds on (most cited first, 12 of 12)

- [Supervised learning with quantum enhanced feature spaces](https://mlsanity.com/paper/1804.11326/) (2018)
- [Universal Approximation with Deep Narrow Networks](https://mlsanity.com/paper/1905.08539/) (2019)
- [Quantum-enhanced machine learning](https://mlsanity.com/paper/1610.08251/) (2016)
- [The non-convex Burer-Monteiro approach works on smooth semidefinite programs](https://mlsanity.com/paper/1606.04970/) (2016)
- [Quantum Neuron: an elementary building block for machine learning on quantum computers](https://mlsanity.com/paper/1711.11240/) (2017)
- [Quantum Perceptron Models](https://mlsanity.com/paper/1602.04799/) (2016)
- [Quantum autoencoders via quantum adders with genetic algorithms](https://mlsanity.com/paper/1709.07409/) (2017)
- [A Riemannian low-rank method for optimization over semidefinite matrices with block-diagonal constraints](https://mlsanity.com/paper/1506.00575/) (2015)
- [Experimental Implementation of a Quantum Autoencoder via Quantum Adders](https://mlsanity.com/paper/1807.10643/) (2018)
- [Feature Learning with Gaussian Restricted Boltzmann Machine for Robust Speech Recognition](https://mlsanity.com/paper/1309.6176/) (2013)
- [Restricted Boltzmann Machine for Classification with Hierarchical Correlated Prior](https://mlsanity.com/paper/1406.3407/) (2014)
- [Pattern Views: Concept and Tooling for Interconnected Pattern Languages](https://mlsanity.com/paper/2003.09127/) (2020)

## Built on by (most cited first, 1 of 1)

- [QOuLiPo: What a quantum computer sees when it reads a book](https://mlsanity.com/paper/2605.14188/) (2026)

## Abstract (arXiv)

Quantum computers are becoming real. Therefore, it is promising to use their potentials in different applications areas, which includes research in the humanities. Due to an increasing amount of data that needs to be processed in the digital humanities the use of quantum computers can contribute to this research area. To give an impression on how beneficial such involvement of quantum computers can be when analyzing data from the humanities, a use case from the media science is presented. Therefore, both the theoretical basis and the tooling support for analyzing the data from our digital humanities project MUSE is described. This includes a data analysis pipeline, containing e.g. various approaches for data preparation, feature engineering, clustering, and classification where several steps can be realized classically, but also supported by quantum computers.