Andrew Tulloch Blance's Outputs (5)

Quantum optimization of complex systems with a quantum annealer (2022)
Journal Article
Abel, S., Blance, A., & Spannowsky, M. (2022). Quantum optimization of complex systems with a quantum annealer. Physical Review A, 106(4), https://doi.org/10.1103/physreva.106.042607

We perform an in-depth comparison of quantum annealing with several classical optimization techniques, namely, thermal annealing, Nelder-Mead, and gradient descent. The focus of our study is large quasicontinuous potentials that must be encoded using... Read More about Quantum optimization of complex systems with a quantum annealer.

Unsupervised event classification with graphs on classical and photonic quantum computers (2021)
Journal Article
Blance, A., & Spannowsky, M. (2021). Unsupervised event classification with graphs on classical and photonic quantum computers. Journal of High Energy Physics, 2021(8), https://doi.org/10.1007/jhep08%282021%29170

Photonic Quantum Computers provide several benefits over the discrete qubit-based paradigm of quantum computing. By using the power of continuous-variable computing we build an anomaly detection model to use on searches for New Physics. Our model use... Read More about Unsupervised event classification with graphs on classical and photonic quantum computers.

Quantum machine learning for particle physics using a variational quantum classifier (2021)
Journal Article
Blance, A., & Spannowsky, M. (2021). Quantum machine learning for particle physics using a variational quantum classifier. Journal of High Energy Physics, 2021, Article 212. https://doi.org/10.1007/jhep02%282021%29212

Quantum machine learning aims to release the prowess of quantum computing to improve machine learning methods. By combining quantum computing methods with classical neural network techniques we aim to foster an increase of performance in solving clas... Read More about Quantum machine learning for particle physics using a variational quantum classifier.

Novel B-decay signatures of light scalars at high energy facilities (2019)
Journal Article
Blance, A., Chala, M., Ramos, M., & Spannowsky, M. (2019). Novel B-decay signatures of light scalars at high energy facilities. Physical Review D, 100(11), Article 115015. https://doi.org/10.1103/physrevd.100.115015

We study the phenomenology of light scalars of masses m1 and m2 coupling to heavy flavor-violating vector bosons of mass mV. For m1;2 ≲ few GeV, this scenario triggers the rare B meson decays B0s → 3μþ3μ−, B0 → 3μþ3μ−, Bþ → Kþ3μþ3μ−, and B0s → K03μþ3... Read More about Novel B-decay signatures of light scalars at high energy facilities.

Adversarially-trained autoencoders for robust unsupervised new physics searches (2019)
Journal Article
Blance, A., Spannowsky, M., & Waite, P. (2019). Adversarially-trained autoencoders for robust unsupervised new physics searches. Journal of High Energy Physics, 2019(10), Article 047. https://doi.org/10.1007/jhep10%282019%29047

Machine learning techniques in particle physics are most powerful when they are trained directly on data, to avoid sensitivity to theoretical uncertainties or an underlying bias on the expected signal. To be able to train on data in searches for new... Read More about Adversarially-trained autoencoders for robust unsupervised new physics searches.