Publications

Order by: publication date number of citations

• Hypercharge quantisation and Fermat's last theorem

  Nakarin Lohitsiri, David Tong

  SciPost Phys. 8, 009 (2020) · published 23 January 2020 | Toggle abstract · pdf

  What values of the Standard Model hypercharges result in a mathematically consistent quantum field theory? We show that the constraints imposed by the lack of gauge anomalies can be recast as the equation x^3 + y^3 = z^3. If hypercharge is quantised, then x, y and z must be integers. The trivial (and only) solutions, with x=0 or y=0, reproduce the hypercharge assignments seen in Nature. This argument does not rely on the mixed gauge-gravitational anomaly, which is automatically vanishing if hypercharge is quantised and the gauge anomalies vanish.

  5 citations

• Pseudoscalar pair production via off-shell Higgs in composite Higgs models

  Diogo Buarque Franzosi, Gabriele Ferretti, Li Huang, Jing Shu

  SciPost Phys. 9, 077 (2020) · published 20 November 2020 | Toggle abstract · pdf

  We propose a new type of search for a pseudoscalar particle $\eta$ pair produced via an off-shell Higgs, $pp\to h^*\to \eta\eta$. The search is motivated by a composite Higgs model in which the $\eta$ is extremely narrow and decays almost exclusively into $Z\gamma$ in the mass range $65$ GeV$\lesssim m_\eta \lesssim 160$ GeV. We devise an analysis strategy to observe the novel $Z\gamma Z\gamma$ channel and estimate potential bounds on the Higgs-$\eta$ coupling. The experimental sensitivity to the signatures depends on the power to identify fake photons and on the ability to predict large photon multiplicities. This search allows us to exclude large values of the compositeness scale $f$, being thus complementary to other typical processes.

  5 citations

• Traveling-wave antenna model for terahertz radiation from laser-plasma interactions

  Jiayu Zhao, Qining Wang, Yuchen Hui, Yamin Chen, Feifan Zhu, Zuanming Jin, Alexander P. Shkurinov, Yan Peng, Yiming Zhu, Songlin Zhuang, Li Lao

  SciPost Phys. Core 5, 046 (2022) · published 29 September 2022 | Toggle abstract · pdf

  Generation of terahertz (THz) wave from air plasma induced by femtosecond laser pulses with a single central frequency (the so-called “single-color”) is one of the fundamental interactions between light and matter, and is also the basis of subsequent pumping schemes using two- or multi-color laser fields. Recently, more states of media beyond gas (e.g., atomic cluster and liquid) via photo-ionization have brought new experimental observations of THz radiation, which can no longer be simply attributed to the mainstream model of the transition-Cherenkov radiation (TCR), thus making the whole picture unclear. Here, we revisited the mechanism of this dynamic process in a new view of the traveling-wave antenna (TWA) model. By successfully reproducing the reported far-field THz radiation profiles from various plasma filament arrangements, the wide applicability of the TWA theory has been revealed. On the other hand in the microscopic view, we investigated the plasma oscillation during filamentation aiming at further bridging the plasma filament and the antenna. Accordingly, THz-plasma resonance has been theoretically and experimentally demonstrated as the elementary THz emitter, paving the way towards fully understanding this important single-color plasma based THz source.

  5 citations

• Higher-order corrections to exclusive heavy vector meson production

  Tuomas Lappi, Heikki Mäntysaari, Jani Penttala

  SciPost Phys. Proc. 8, 133 (2022) · published 14 July 2022 | Toggle abstract · pdf

  We present results for higher-order corrections to exclusive $\mathrm{J}/\psi$ production. This includes the first relativistic correction of order $v^2$ in quark velocity, and next-to-leading order corrections in $\alpha_s$ for longitudinally polarized production. The relativistic corrections are found to be important for a good description of the HERA data, especially at small values of the photon virtuality. The next-to-leading order results for longitudinal production are evaluated numerically. We also demonstrate how the vector meson production provides complementary information to the structure functions for extracting the initial condition for the small-$x$ evolution of the dipole-proton scattering amplitude.

  5 citations

• The SpinParser software for pseudofermion functional renormalization group calculations on quantum magnets

  Finn Lasse Buessen

  SciPost Phys. Codebases 5 (2022) · published 24 August 2022 | Toggle abstract · pdf

  We present the SpinParser open-source software [ https://github.com/fbuessen/SpinParser ]. The software is designed to perform pseudofermion functional renormalization group (pf-FRG) calculations for frustrated quantum magnets in two and three spatial dimensions. It aims to make such calculations readily accessible without the need to write specialized program code; instead, custom lattice graphs and microscopic spin models can be defined as plain-text input files. Underlying symmetries of the model are automatically analyzed and exploited by the numerical core written in C++ in order to optimize the performance across large-scale shared memory and/or distributed memory computing platforms.

  5 citations

• Magnetisation and Mean Field Theory in the Ising Model

  Dalton A R Sakthivadivel

  SciPost Phys. Lect. Notes 35 (2022) · published 19 January 2022 | Toggle abstract · pdf

  In this set of notes, a complete, pedagogical tutorial for applying mean field theory to the two-dimensional Ising model is presented. Beginning with the motivation and basis for mean field theory, we formally derive the Bogoliubov inequality and discuss mean field theory itself. We proceed with the use of mean field theory to determine a magnetisation function, and the results of the derivation are interpreted graphically, physically, and mathematically. We give a new interpretation of the self-consistency condition in terms of intersecting surfaces and constrained solution sets. We also include some more general comments on the thermodynamics of the phase transition. We end by evaluating symmetry considerations in magnetisation, and some more subtle features of the Ising model. Together, a self-contained overview of the mean field Ising model is given, with some novel presentation of important results.

  5 citations

• On the generalizability of artificial neural networks in spin models

  Hon Man Yau, Nan Su

  SciPost Phys. Core 5, 032 (2022) · published 8 June 2022 | Toggle abstract · pdf

  The applicability of artificial neural networks (ANNs) is typically limited to the models they are trained with and little is known about their generalizability, which is a pressing issue in the practical application of trained ANNs to unseen problems. Here, by using the task of identifying phase transitions in spin models, we establish a systematic generalizability such that simple ANNs trained with the two-dimensional ferromagnetic Ising model can be applied to the ferromagnetic q-state Potts model in different dimensions for q>=2. The same scheme can be applied to the highly nontrivial antiferromagnetic q-state Potts model. We demonstrate that similar results can be obtained by reducing the exponentially large state space spanned by the training data to one that comprises only three representative configurations artificially constructed through symmetry considerations. We expect our findings to simplify and accelerate the development of machine learning-assisted tasks in spin-model related disciplines in physics and materials science.

  5 citations

• Anomaly Awareness

  Charanjit K. Khosa, Veronica Sanz

  SciPost Phys. 15, 053 (2023) · published 8 August 2023 | Toggle abstract · pdf

  We present a new algorithm for anomaly detection called Anomaly Awareness. The algorithm learns about normal events while being made aware of the anomalies through a modification of the cost function. We show how this method works in different Particle Physics situations and in standard Computer Vision tasks. For example, we apply the method to images from a Fat Jet topology generated by Standard Model Top and QCD events, and test it against an array of new physics scenarios, including Higgs production with EFT effects and resonances decaying into two, three or four subjets. We find that the algorithm is effective identifying anomalies not seen before, and becomes robust as we make it aware of a varied-enough set of anomalies.

  5 citations

• Detecting nematic order in STM/STS data with artificial intelligence

  Jeremy B. Goetz, Yi Zhang, Michael J. Lawler

  SciPost Phys. 8, 087 (2020) · published 15 June 2020 | Toggle abstract · pdf

  Detecting the subtle yet phase defining features in Scanning Tunneling Microscopy and Spectroscopy data remains an important challenge in quantum materials. We meet the challenge of detecting nematic order from local density of states data with supervised machine learning and artificial neural networks for the difficult scenario without sharp features such as visible lattice Bragg peaks or Friedel oscillation signatures in the Fourier transform spectrum. We train the artificial neural networks to classify simulated data of isotropic and anisotropic two-dimensional metals in the presence of disorder. The supervised machine learning succeeds only with at least one hidden layer in the ANN architecture, demonstrating it is a higher level of complexity than nematic order detected from Bragg peaks which requires just two neurons. We apply the finalized ANN to experimental STM data on CaFe2As2, and it predicts nematic symmetry breaking with 99% confidence (probability 0.99), in agreement with previous analysis. Our results suggest ANNs could be a useful tool for the detection of nematic order in STM data and a variety of other forms of symmetry breaking.

  5 citations

• "Spectrally gapped" random walks on networks: a Mean First Passage Time formula

  Silvia Bartolucci, Fabio Caccioli, Francesco Caravelli, Pierpaolo Vivo

  SciPost Phys. 11, 088 (2021) · published 4 November 2021 | Toggle abstract · pdf

  We derive an approximate but explicit formula for the Mean First Passage Time of a random walker between a source and a target node of a directed and weighted network. The formula does not require any matrix inversion, and it takes as only input the transition probabilities into the target node. It is derived from the calculation of the average resolvent of a deformed ensemble of random sub-stochastic matrices $H=\langle H\rangle +\delta H$, with $\langle H\rangle$ rank-$1$ and non-negative. The accuracy of the formula depends on the spectral gap of the reduced transition matrix, and it is tested numerically on several instances of (weighted) networks away from the high sparsity regime, with an excellent agreement.

  5 citations