Professor Michael Spannowsky's Outputs (201)

Generating quantum reservoir state representations with random matrices (2025)
Journal Article
Tovey, S., Fellner, T., Holm, C., & Spannowsky, M. (2025). Generating quantum reservoir state representations with random matrices. Machine Learning: Science and Technology, 6(1), Article 015068. https://doi.org/10.1088/2632-2153/adc0e2

We demonstrate a novel approach to reservoir computation measurements using random matrices. We do so to motivate how atomic-scale devices could be used for real-world computational applications. Our approach uses random matrices to construct reservo... Read More about Generating quantum reservoir state representations with random matrices.

Optimal equivariant architectures from the symmetries of matrix-element likelihoods (2025)
Journal Article
Maître, D., Ngairangbam, V. S., & Spannowsky, M. (2025). Optimal equivariant architectures from the symmetries of matrix-element likelihoods. Machine Learning: Science and Technology, 6(1), Article 015059. https://doi.org/10.1088/2632-2153/adbab1

The Matrix-Element Method (MEM) has long been a cornerstone of data analysis in high-energy physics. It leverages theoretical knowledge of parton-level processes and symmetries to evaluate the likelihood of observed events. In parallel, the advent of... Read More about Optimal equivariant architectures from the symmetries of matrix-element likelihoods.

Probing right-handed neutrinos via trilepton signals at the HL-LHC (2025)
Journal Article
Mitra, M., Saha, S., Spannowsky, M., & Takeuchi, M. (2025). Probing right-handed neutrinos via trilepton signals at the HL-LHC. Physical Review D, 111(1), Article 015005. https://doi.org/10.1103/PhysRevD.111.015005

Neutrino oscillation experiments have provided direct evidence for the existence of neutrino masses. The seesaw mechanism explains the smallness of these masses through the introduction of heavy right-handed neutrino (RHN) states. The RHN states can... Read More about Probing right-handed neutrinos via trilepton signals at the HL-LHC.

Electroweak corrections and EFT operators in W+W− production at the LHC (2024)
Journal Article
Banerjee, S., Reichelt, D., & Spannowsky, M. (2024). Electroweak corrections and EFT operators in W+W− production at the LHC. Physical Review D, 110(11), https://doi.org/10.1103/physrevd.110.115012

We investigate the impact of electroweak corrections and effective field theory operators on WþW− production at the Large Hadron Collider (LHC). Utilizing the Standard Model effective-field theory (SMEFT) framework, we extend the Standard Model by in... Read More about Electroweak corrections and EFT operators in W+W− production at the LHC.

Enhancing quantum field theory simulations on NISQ devices with Hamiltonian truncation (2024)
Journal Article
Ingoldby, J., Spannowsky, M., Sypchenko, T., & Williams, S. (2024). Enhancing quantum field theory simulations on NISQ devices with Hamiltonian truncation. Physical Review D, 110(9), Article 096016. https://doi.org/10.1103/physrevd.110.096016

Quantum computers can efficiently simulate highly entangled quantum systems, offering a solution to challenges facing classical simulation of quantum field theories (QFTs). This paper presents an alternative to traditional methods for simulating the... Read More about Enhancing quantum field theory simulations on NISQ devices with Hamiltonian truncation.

Equivariant, safe and sensitive — graph networks for new physics (2024)
Journal Article
Bhardwaj, A., Englert, C., Naskar, W., Ngairangbam, V. S., & Spannowsky, M. (2024). Equivariant, safe and sensitive — graph networks for new physics. Journal of High Energy Physics, 2024(7), Article 245. https://doi.org/10.1007/jhep07%282024%29245

This study introduces a novel Graph Neural Network (GNN) architecture that leverages infrared and collinear (IRC) safety and equivariance to enhance the analysis of collider data for Beyond the Standard Model (BSM) discoveries. By integrating equivar... Read More about Equivariant, safe and sensitive — graph networks for new physics.

Dispelling the L myth for the High-Luminosity LHC (2024)
Journal Article
Belvedere, A., Englert, C., Kogler, R., & Spannowsky, M. (2024). Dispelling the L myth for the High-Luminosity LHC. The European Physical Journal C, 84(7), Article 715. https://doi.org/10.1140/epjc/s10052-024-13032-w

Extrapolations of sensitivity to new interactions and standard model parameters critically inform the programme at the Large Hadron Collider (LHC) and potential future collider cases. To this end, statistical considerations based on inclusive quantit... Read More about Dispelling the L myth for the High-Luminosity LHC.

Simulating quantum field theories on continuous-variable quantum computers (2024)
Journal Article
Abel, S., Spannowsky, M., & Williams, S. (2024). Simulating quantum field theories on continuous-variable quantum computers. Physical Review A, 110(1), Article 012607. https://doi.org/10.1103/physreva.110.012607

We delve into the use of photonic quantum computing to simulate quantum mechanics and extend its application towards quantum field theory. We develop and prove a method that leverages this form of continuous-variable quantum computing (CVQC) to repro... Read More about Simulating quantum field theories on continuous-variable quantum computers.

Training neural networks with universal adiabatic quantum computing (2024)
Journal Article
Abel, S., Criado, J. C., & Spannowsky, M. (2024). Training neural networks with universal adiabatic quantum computing. Frontiers in Artificial Intelligence, 7, Article 1368569. https://doi.org/10.3389/frai.2024.1368569

The training of neural networks (NNs) is a computationally intensive task requiring significant time and resources. This article presents a novel approach to NN training using adiabatic quantum computing (AQC), a paradigm that leverages the principle... Read More about Training neural networks with universal adiabatic quantum computing.

Exploring thermal equilibria of the Fermi-Hubbard model with variational quantum algorithms (2024)
Journal Article
Araz, J. Y., Spannowsky, M., & Wingate, M. (2024). Exploring thermal equilibria of the Fermi-Hubbard model with variational quantum algorithms. Physical Review A, 109(6), Article 062422. https://doi.org/10.1103/physreva.109.062422

This study investigates the thermal properties of the repulsive Fermi-Hubbard model with chemical potential using variational quantum algorithms, crucial in comprehending particle behavior within lattices at high temperatures in condensed matter syst... Read More about Exploring thermal equilibria of the Fermi-Hubbard model with variational quantum algorithms.

Generative invertible quantum neural networks (2024)
Journal Article
Rousselot, A., & Spannowsky, M. (2024). Generative invertible quantum neural networks. SciPost Physics, 16(6), Article 146. https://doi.org/10.21468/scipostphys.16.6.146

Invertible Neural Networks (INN) have become established tools for the simulation and generation of highly complex data. We propose a quantum-gate algorithm for a Quantum Invertible Neural Network (QINN) and apply it to the LHC data of jet-associated... Read More about Generative invertible quantum neural networks.

Quantum pathways for charged track finding in high-energy collisions (2024)
Journal Article
Brown, C., Spannowsky, M., Tapper, A., Williams, S., & Xiotidis, I. (2024). Quantum pathways for charged track finding in high-energy collisions. Frontiers in Artificial Intelligence, 7, Article 1339785. https://doi.org/10.3389/frai.2024.1339785

In high-energy particle collisions, charged track finding is a complex yet crucial endeavor. We propose a quantum algorithm, specifically quantum template matching, to enhance the accuracy and efficiency of track finding. Abstracting the Quantum Ampl... Read More about Quantum pathways for charged track finding in high-energy collisions.

Higgs boson off-shell measurements probe nonlinearities (2024)
Journal Article
Anisha, Englert, C., Kogler, R., & Spannowsky, M. (2024). Higgs boson off-shell measurements probe nonlinearities. Physical Review D, 109(9), Article 095033. https://doi.org/10.1103/physrevd.109.095033

The measurements of off-shell Higgs boson contributions in massive gauge boson pair production are known to probe its electroweak interactions across different energy scales. Often employed as an estimator of the Higgs boson width in restricted theor... Read More about Higgs boson off-shell measurements probe nonlinearities.

Charting the free energy landscape of metastable topological magnetic objects (2024)
Journal Article
Criado, J. C., Hatton, P. D., Lanza, Á., Schenk, S., & Spannowsky, M. (2024). Charting the free energy landscape of metastable topological magnetic objects. Physical Review B, 109(19), Article 195114. https://doi.org/10.1103/physrevb.109.195114

Chiral magnets with Dzyaloshinskii-Moriya interactions feature a rich phase diagram with a variety of thermodynamical phases. These include helical and conical spin arrangements and topologically charged objects such as (anti)Skyrmions. Crucially, du... Read More about Charting the free energy landscape of metastable topological magnetic objects.

Interpretable deep learning models for the inference and classification of LHC data (2024)
Journal Article
Ngairangbam, V. S., & Spannowsky, M. (2024). Interpretable deep learning models for the inference and classification of LHC data. Journal of High Energy Physics, 2024(5), Article 4. https://doi.org/10.1007/jhep05%282024%29004

The Shower Deconstruction methodology is pivotal in distinguishing signal and background jets, leveraging the detailed information from perturbative parton showers. Rooted in the Neyman-Pearson lemma, this method is theoretically designed to differen... Read More about Interpretable deep learning models for the inference and classification of LHC data.

Three-Body Entanglement in Particle Decays. (2024)
Journal Article
Sakurai, K., & Spannowsky, M. (2024). Three-Body Entanglement in Particle Decays. Physical Review Letters, 132(15), Article 151602. https://doi.org/10.1103/PhysRevLett.132.151602

Quantum entanglement has long served as a foundational pillar in understanding quantum mechanics, with a predominant focus on two-particle systems. We extend the study of entanglement into the realm of three-body decays, offering a more intricate und... Read More about Three-Body Entanglement in Particle Decays..

EFT, decoupling, Higgs boson mixing, and higher dimensional operators (2024)
Journal Article
Banerjee, U., Chakrabortty, J., Englert, C., Naskar, W., Rahaman, S. U., & Spannowsky, M. (2024). EFT, decoupling, Higgs boson mixing, and higher dimensional operators. Physical Review D, 109(5), Article 055035. https://doi.org/10.1103/physrevd.109.055035

The effective field theory (EFT) framework is a precise approximation procedure when the inherent assumptions of a large-scale separation between the Standard Model (SM) and new interactions alongside perturbativity are realized. Constraints from ava... Read More about EFT, decoupling, Higgs boson mixing, and higher dimensional operators.

Simulating Z 2 lattice gauge theory with the variational quantum thermalizer (2024)
Journal Article
Fromm, M., Philipsen, O., Spannowsky, M., & Winterowd, C. (2024). Simulating Z 2 lattice gauge theory with the variational quantum thermalizer. EPJ Quantum Technology, 11(1), 20. https://doi.org/10.1140/epjqt/s40507-024-00232-2

The properties of strongly-coupled lattice gauge theories at finite density as well as in real time have largely eluded first-principles studies on the lattice. This is due to the failure of importance sampling for systems with a complex action. An a... Read More about Simulating Z 2 lattice gauge theory with the variational quantum thermalizer.

Prospects for exotic h→4τ decays in single and di-Higgs boson production at the LHC and future hadron colliders (2024)
Journal Article
Adhikary, A., Banerjee, S., Barman, R. K., Batell, B., Bhattacherjee, B., Bose, C., Qian, Z., & Spannowsky, M. (2024). Prospects for exotic h→4τ decays in single and di-Higgs boson production at the LHC and future hadron colliders. Physical Review D, 109(5), Article 055008. https://doi.org/10.1103/physrevd.109.055008

We study the prospects for observing exotic decays of the Standard Model Higgs boson h into light beyond the Standard Model scalars a with mass ma≲mh/2 in the single Higgs and Higgs pair production channels at the high luminosity run of the Large Had... Read More about Prospects for exotic h→4τ decays in single and di-Higgs boson production at the LHC and future hadron colliders.

Hypergraphs in LHC phenomenology — the next frontier of IRC-safe feature extraction (2024)
Journal Article
Konar, P., Ngairangbam, V. S., & Spannowsky, M. (2024). Hypergraphs in LHC phenomenology — the next frontier of IRC-safe feature extraction. Journal of High Energy Physics, 2024(1), Article 113. https://doi.org/10.1007/jhep01%282024%29113

In this study, we critically evaluate the approximation capabilities of existing infra-red and collinear (IRC) safe feature extraction algorithms, namely Energy Flow Networks (EFNs) and Energy-weighted Message Passing Networks (EMPNs). Our analysis r... Read More about Hypergraphs in LHC phenomenology — the next frontier of IRC-safe feature extraction.