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Welcome to Durham Research Online (DRO)

Durham Research Online (DRO) is the University’s Open Access repository for publications. The primary purpose of DRO is to provide open access to publications authored by staff and students affiliated with Durham University.

See our Policies page for further information.



Latest Additions

Enhanced Quantum Control of Individual Ultracold Molecules Using Optical Tweezer Arrays (2024)
Journal Article
Ruttley, D. K., Guttridge, A., Hepworth, T. R., & Cornish, S. L. (2024). Enhanced Quantum Control of Individual Ultracold Molecules Using Optical Tweezer Arrays. PRX Quantum, 5(2), Article 020333. https://doi.org/10.1103/prxquantum.5.020333

Control over the quantum states of individual molecules is crucial in the quest to harness their rich internal structure and dipolar interactions for applications in quantum science. In this paper, we develop a toolbox of techniques for the control a... Read More about Enhanced Quantum Control of Individual Ultracold Molecules Using Optical Tweezer Arrays.

Wave-Function Network Description and Kolmogorov Complexity of Quantum Many-Body Systems (2024)
Journal Article
Mendes-Santos, T., Schmitt, M., Angelone, A., Rodriguez, A., Scholl, P., Williams, H., …Dalmonte, M. (2024). Wave-Function Network Description and Kolmogorov Complexity of Quantum Many-Body Systems. Physical Review X, 14(2), Article 021029. https://doi.org/10.1103/physrevx.14.021029

Programmable quantum devices are now able to probe wave functions at unprecedented levels. This is based on the ability to project the many-body state of atom and qubit arrays onto a measurement basis which produces snapshots of the system wave funct... Read More about Wave-Function Network Description and Kolmogorov Complexity of Quantum Many-Body Systems.

Microlensing signatures of extended dark objects using machine learning (2024)
Journal Article
Crispim Romao, M., & Croon, D. (2024). Microlensing signatures of extended dark objects using machine learning. Physical Review D, 109(12), Article 123004. https://doi.org/10.1103/physrevd.109.123004

This paper presents a machine learning-based method for the detection of the unique gravitational microlensing signatures of extended dark objects, such as boson stars, axion miniclusters and subhalos. We adapt MicroLIA, a machine learning-based pack... Read More about Microlensing signatures of extended dark objects using machine learning.

Combining evolutionary strategies and novelty detection to go beyond the alignment limit of the Z3 3HDM (2024)
Journal Article
Crispim Romão, J., & Crispim Romão, M. (2024). Combining evolutionary strategies and novelty detection to go beyond the alignment limit of the Z3 3HDM. Physical Review D, 109(9), Article 095040. https://doi.org/10.1103/physrevd.109.095040

We present a novel artificial intelligence approach for beyond the Standard Model parameter space scans by augmenting an evolutionary strategy with novelty detection. Our approach leverages the power of evolutionary strategies, previously shown to qu... Read More about Combining evolutionary strategies and novelty detection to go beyond the alignment limit of the Z3 3HDM.