Publications

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Numerical aspects of large deviations

Alexander K. Hartmann

SciPost Phys. Lect. Notes 100 (2025) · published 30 September 2025 | · pdf

An introduction to numerical large-deviation sampling is provided. First, direct biasing with a known distribution is explained. As simple example, the Bernoulli process is used throughout the text. Next, Markov chain Monte Carlo (MCMC) simulations are introduced. In particular, the Metropolis-Hastings algorithm is explained. As first implementation of MCMC, sampling of the plain Bernoulli model is shown. Next, an exponential bias is used for the same model, which allows one to obtain the tails of the distribution of a measurable quantity. This approach is generalized to MCMC simulations, where the states are vectors of $U(0,1)$ random entries. This allows one to use the exponential or any other bias to access the large-deviation properties of rather arbitrary random processes. Finally, some recent research applications to study more complex models are discussed.
Fast tensor disentangling algorithm

Kevin Slagle

SciPost Phys. 11, 056 (2021) · published 13 September 2021 | · pdf

Many recent tensor network algorithms apply unitary operators to parts of a tensor network in order to reduce entanglement. However, many of the previously used iterative algorithms to minimize entanglement can be slow. We introduce an approximate, fast, and simple algorithm to optimize disentangling unitary tensors. Our algorithm is asymptotically faster than previous iterative algorithms and often results in a residual entanglement entropy that is within 10 to 40% of the minimum. For certain input tensors, our algorithm returns an optimal solution. When disentangling order-4 tensors with equal bond dimensions, our algorithm achieves an entanglement spectrum where nearly half of the singular values are zero. We further validate our algorithm by showing that it can efficiently disentangle random 1D states of qubits.
Dark Matter searches with the ATLAS Detector

Guglielmo Frattari

SciPost Phys. Proc. 8, 085 (2022) · published 12 July 2022 | · pdf

The presence of a non-baryonic dark matter (DM) component in the Universe is inferred from the observation of its gravitational interaction. If dark matter interacts weakly with the Standard Model (SM) it could be produced at the LHC. The ATLAS experiment has developed a broad search program for DM candidates, including resonance searches for the mediator which would couple DM to the SM. The results of recent searches on 13 TeV pp data, their interplay and interpretation will be presented. Prospects for HL-LHC will also be discussed.
Status and prospects of the JUNO experiment

Matthias Raphael Stock, on behalf of the JUNO collaboration

SciPost Phys. Proc. 17, 020 (2025) · published 23 July 2025 | · pdf

The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment currently under construction in China. It is located 52.5 km away from two nuclear power plants in a newly constructed 700-m-deep underground laboratory. JUNO will be the largest liquid scintillator (LS) detector in the world comprising 20 kt of ultra-pure LS filled in an acrylic sphere. Its main goal is to determine the neutrino mass ordering by measuring the energy spectrum of reactor neutrinos with highest accuracy. In addition, JUNO will cover precision measurements of oscillation parameters and several aspects in the field of astroparticle physics. Data taking will start in late 2024.
Topological-insulator nanocylinders

Michele Governale, Fabio Taddei

SciPost Phys. Core 6, 032 (2023) · published 21 April 2023 | · pdf

Nanostructures, such a quantum dots or nanoparticles, made of three-dimensional topological insulators (3DTIs) have been recently attracting increasing interest, especially for their optical properties. In this paper we calculate the energy spectrum, the surface states and the dipole matrix elements for optical transitions with in-plane polarization of 3DTI nanocylinders of finite height $L$ and radius $R$. We first derive an effective 2D Hamiltonian by exploiting the cylindrical symmetry of the problem. We develop two approaches: the first one is an exact numerical tight-binding model obtained by discretising the Hamiltonian. The second one, which allows us to obtain analytical results, is an approximated model based on a large-$R$ expansion and on an effective boundary condition to account for the finite height of the nanocylinder. We find that the agreement between the two models, as far as eigenenergies and eigenfunctions are concerned, is excellent for the lowest absolute value of the longitudinal component of the angular momentum. Finally, we derive analytical expressions for the dipole matrix elements by first considering the lateral surface alone and the bases alone, and then for the whole nanocylinder. In particular, we focus on the two limiting cases of tall and squat nanocylinders. The latter case is compared with the numerical results finding a good agreement.
Prompt hadroproduction of C-even quarkonia in the light-front $k_T$ -factorization approach

Wolfgang Schäfer, Izabela Babiarz, Roman Pasechnik, Antoni Szczurek

SciPost Phys. Proc. 8, 032 (2022) · published 11 July 2022 | · pdf

We present a new approach for the prompt production of quarkonia which is based on the $k_T$-factorization method. The production of even C-parity quarkonia proceeds via the fusion of two (off-shell) gluons. Especially in the kinematics of the LHCb experiment these processes are thus expected to be a sensitive probe of the small-x gluon distribution. We calculate the relevant off-shell matrix elements in terms of the light-front wave functions of the quarkonium states. We present our results for scalar and pseudoscalar charmonia and discuss photon transition form factors as well as cross sections for prompt hadroproduction. We compare our results for the $\eta_c$ to recent LHCb data.
Analytical expression for $\pi$-ton vertex contributions to the optical conductivity

Juraj Krsnik, Anna Kauch, Karsten Held

SciPost Phys. 18, 138 (2025) · published 25 April 2025 | · pdf

Vertex corrections from the transversal particle-hole channel, so-called $\pi$-tons, are generic in models for strongly correlated electron systems and can lead to a displaced Drude peak (DDP). Here, we derive the analytical expression for these $\pi$-tons, and how they affect the optical conductivity as a function of correlation length $\xi$, fermion lifetime $\tau$, temperature $T$, and coupling strength to spin or charge fluctuations $g$. In particular, for $T\rightarrow T_c$, the critical temperature for antiferromagnetic or charge ordering, the dc vertex correction is algebraic $\sigma_{VERT}^{dc}\propto \xi \sim (T-T_c)^{-\nu}$ in one dimension and logarithmic $\sigma_{VERT}^{dc}\propto \ln\xi \sim \nu \ln (T-T_c)$ in two dimensions. Here, $\nu$ is the critical exponent for the correlation length. If we have the exponential scaling $\xi \sim e^{1/T}$ of an ideal two-dimensional system, the DDP becomes more pronounced with increasing $T$ but fades away at low temperatures where only a broadening of the Drude peak remains, as it is observed experimentally, with the dc resistivity exhibiting a linear $T$ dependence at low temperatures. Further, we find the maximum of the DPP to be given by the inverse lifetime: $\omega_{DDP} \sim 1/\tau$. These characteristic dependencies can guide experiments to evidence $\pi$-tons in actual materials.
Probing ALPs at the LUXE experiment

Federico Meloni on behalf of the LUXE collaboration

SciPost Phys. Proc. 12, 037 (2023) · published 4 July 2023 | · pdf

The proposed LUXE experiment (LASER Und XFEL Experiment) at DESY, Hamburg, aims to probe QED in its non-perturbative regime. In order to do this, LUXE will study the interactions between 16.5 GeV electrons from the European XFEL and high-intensity laser pulses. This experiment also provides a unique opportunity to probe physics beyond the Standard Model: exploiting the large photon flux generated at LUXE, it is possible to design a dedicated detector to probe axion-like-particles up to a mass of 350 MeV and with photon coupling of $3 \cdot 10^{-6}$ GeV$^{-1}$. This reach is comparable to the projected sensitivity of experiments like FASER2 at the HL-LHC and NA62 operating in dump mode.
Background suppression in the COSINUS experiment: Active muon veto and radiopure materials selection

M. Stukel, G. Angloher, Mukund Raghunath Bharadwaj, I. Dafinei , N. Di Marco, L. Einfalt, F. Ferroni, S. Fichtinger, A. Filipponi, T. Frank, M. Friedl, A. Fuss , Z. Ge, M. Heikinheimo, K. Huitu, M. Kellermann, R. Maji, M. Mancuso, L. Pagnanini, F. Petricca, S. Pirro, F. Pröbst, G. Profeta, A. Puiu, F. Reindl, K. Schäffner, J. Schieck, D. Schmiedmayer, C. Schwertner, M. Stahlberg, A. Stendahl, F. Wagner, S. Yue, V. Zema, Y. Zhu

SciPost Phys. Proc. 12, 032 (2023) · published 4 July 2023 | · pdf

For over twenty-five years the DAMA/LIBRA experiment has reported an annual modulation signal that is consistent with a dark matter explanation. This signal is, currently, in tension with the null results observed by other searches that utilize different target detectors. The COSINUS experiment will perform a model-independent cross-check of the DAMA/LIBRA result by using the same target material, NaI crystals, operated as scintillating calorimeters. By measuring both temperature and light the NaI crystals in COSINUS will be able to distinguish between electron and nuclear recoils on an event-by-event basis. However, background events induced by cosmic-rays, environmental radioactivity or the intrinsic contamination of the materials used in the crystal, shielding and infrastructure can pose an issue to any analysis and must be fully understood. We report on the status of the development of the simulation for an active water Cherenkov muon veto, as well as the results of the beginning radiogenic material screening.
Quantifying the effects of noise in a quantum convolutional neural network

Zeyu Fan, Jonathan Wei Zhong Lau, Leong-Chuan Kwek

SciPost Phys. Core 8, 093 (2025) · published 18 December 2025 | · pdf

This study quantifies the effects of quantum noise on the performance of a quantum convolutional neural network (QCNN), building on parallels with classical convolutional neural networks (CNNs), where added Gaussian noise can improve training speed, accuracy, and generalizability. While such benefits are established for classical CNNs, the influence of noise on quantum counterparts remains insufficiently characterized. We specifically examine three types of quantum noise: decoherence, Gaussian noise arising from imperfect quantum gates and experimental error, and systematic noise introduced during input state preparation. Our analysis provides a detailed assessment of how these distinct noise sources affect QCNN operation and outlines considerations for mitigating their impact. Though a QCNN is used as an example in this work, the methods used here can be applied to other quantum machine learning models as well.

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