Publications

Order by: publication date number of citations

• 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 | Toggle abstract · 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.

• ALICE at the LHC and astrophysics: From providing input for the search for antinuclei in space to constraining the equation of state of neutron stars

  Alexander Kalweit on behalf of the ALICE collaboration

  SciPost Phys. Proc. 13, 022 (2023) · published 29 September 2023 | Toggle abstract · pdf

  The ALICE experiment at the LHC was originally designed to study the creation of the quark-gluon-plasma in heavy-ion collisions, a new state of matter in which quarks and gluons are not confined into hadrons. More recently, the versatility of both the Large Hadron Collider and the ALICE apparatus have given additionally access to a unique set of nuclear and hadronic physics measurements. The main results from this new and dynamic research area will be presented. The application of these findings to astrophysical challenges, ranging from the equation of state of neutron stars to the search for dark matter in space, will be discussed.

• Quantum adiabaticity in many-body systems and almost-orthogonality in complementary subspace

  Jyong-Hao Chen, Vadim Cheianov

  SciPost Phys. Core 8, 084 (2025) · published 12 November 2025 | Toggle abstract · pdf

  We investigate why, in quantum many-body systems, the adiabatic fidelity and the overlap between the initial state and instantaneous ground states often yield nearly identical values. Our analysis suggests that this phenomenon results from an interplay between two intrinsic limits of many-body systems: the limit of small evolution parameters and the limit of large system sizes. In the former case, conventional perturbation theory provides a straightforward explanation. In the latter case, a key insight is that pairs of vectors in the Hilbert space orthogonal to the initial state tend to become nearly orthogonal as the system size increases. We illustrate these general findings with two representative models of driven many-body systems: the driven Rice-Mele model and the driven interacting Kitaev chain model.

• Forward proton measurements with ATLAS

  Mustafa Schmidt

  SciPost Phys. Proc. 15, 008 (2024) · published 2 April 2024 | Toggle abstract · pdf

  The ALFA subdetector is designed to measure elastic proton-proton scattering from which the total cross section and $\rho$-parameter are determined. In 2016, special runs at a center-of-mass energy of $\sqrt{s}$ = 13 TeV and with $\beta^\star$ = 2.5 km were recorded.

• Cryptographic tests of the python’s lunch conjecture

  Alex May, Sabrina Pasterski, Chris Waddell, Michelle Xu

  SciPost Phys. 19, 084 (2025) · published 2 October 2025 | Toggle abstract · pdf

  In the AdS/CFT correspondence, a subregion of the CFT allows for the recovery of a corresponding subregion of the bulk known as its entanglement wedge. In some cases, an entanglement wedge contains a locally but not globally minimal surface homologous to the CFT subregion, in which case it is said to contain a python's lunch. It has been proposed that python's lunch geometries should be modelled by tensor networks that feature projective operations where the wedge narrows. This model leads to the python's lunch (PL) conjecture, which asserts that reconstructing information from past the locally minimal surface is computationally difficult. In this work, we use cryptographic tools related to a primitive known as the Conditional Disclosure of Secrets (CDS) to develop consequences of the projective tensor network model that can be checked directly in AdS/CFT. We argue from the tensor network picture that the mutual information between appropriate CFT subregions is lower bounded linearly by an area difference associated with the geometry of the lunch. Recalling that the mutual information is also computed by bulk extremal surfaces, this gives a checkable geometrical consequence of the tensor network model. We prove weakened versions of this geometrical statement in asymptotically AdS$_{2+1}$ spacetimes satisfying the null energy condition, and confirm it in some example geometries, supporting the tensor network model and by proxy the PL conjecture.

• Instanton density operator in lattice QCD from higher category theory

  Jing-Yuan Chen

  SciPost Phys. 19, 158 (2025) · published 17 December 2025 | Toggle abstract · pdf

  A natural definition for instanton density operator in lattice QCD has long been desired. We show this problem is, and has to be, solved by higher category theory. The problem is solved by refining at a conceptual level the Yang-Mills theory on lattice, in order to recover the homotopy information in the continuum, which would have been lost if we put the theory on lattice in the traditional way. The refinement needed is a generalization—through the lens of higher category theory—of the familiar process of Villainization that captures winding in lattice XY model and Dirac quantization in lattice Maxwell theory. The apparent difference is that Villainization is in the end described by principal bundles, hence familiar, but more general topological operators can only be captured on the lattice by more flexible structures beyond the usual group theory and fibre bundles, making the language of categories natural and necessary. The key structure we need for our particular problem is called multiplicative bundle gerbe, based upon which we can construct suitable structures to naturally define the 2d Wess-Zumino-Witten term, 3d skyrmion density operator and 4d hedgehog defect for lattice $S^3$ (pion vacua) non-linear sigma model, and the 3d Chern-Simons term, 4d instanton density operator and 5d Yang monopole defect for lattice $SU(N)$ Yang-Mills theory; moreover, the structures behind the non-linear sigma model and the Yang-Mills theory are related via an implicit Yang-Baxter equation. In a broader perspective, higher category theory enables us to rethink more systematically the relation between continuum quantum field theory and lattice quantum field theory. We sketch a proposal towards a general machinery that constructs the suitably refined lattice degrees of freedom for a given non-linear sigma model or gauge theory in the continuum, realizing the desired topological operators on the lattice.

• Integrable fishnet circuits and Brownian solitons

  Žiga Krajnik, Enej Ilievski, Tomaž Prosen, Benjamin J. A. Héry, Vincent Pasquier

  SciPost Phys. 19, 027 (2025) · published 21 July 2025 | Toggle abstract · pdf

  We introduce classical many-body dynamics on a one-dimensional lattice comprising local two-body maps arranged on discrete space-time mesh that serve as discretizations of Hamiltonian dynamics with arbitrarily time-varying coupling constants. Time evolution is generated by passing an auxiliary degree of freedom along the lattice, resulting in a 'fishnet' circuit structure. We construct integrable circuits consisting of Yang-Baxter maps and demonstrate their general properties, using the Toda and anisotropic Landau-Lifschitz models as examples. Upon stochastically rescaling time, the dynamics is dominated by fluctuations and we observe solitons undergoing Brownian motion.

• The two critical temperatures conundrum in La$_{1.83}$Sr$_{0.17}$CuO$_4$

  Abhisek Samanta, Itay Mangel, Amit Keren, Daniel P. Arovas, Assa Auerbach

  SciPost Phys. 16, 148 (2024) · published 5 June 2024 | Toggle abstract · pdf

  The in-plane and out-of-plane superconducting stiffness of ${\rm La}^{\vphantom{\dagger}}_{1.83}{\rm Sr}^{\vphantom{\dagger}}_{0.17}{\rm CuO}^{\vphantom{\dagger}}_4$ rings appear to vanish at different transition temperatures, which contradicts thermodynamical expectation. In addition, we observe a surprisingly strong dependence of the out-of-plane stiffness transition on sample width. With evidence from Monte Carlo simulations, this effect is explained by very small ratio $\alpha$ of inter-plane over intra-plane Josephson couplings. For three dimensional rings of millimeter dimensions, a crossover from layered three dimensional to quasi one dimensional behavior occurs at temperatures near the thermodynamic transition temperature ${T_{\rm c}}$, and the out-of-plane stiffness appears to vanish below ${T_{\rm c}}$ by a temperature shift of order $\alpha L_a/{\xi^{\parallel}}$, where $L_a/{\xi^{\parallel}}$ is the sample's width over coherence length. Including the effects of layer-correlated disorder, the measured temperature shifts can be fit by a value of $\alpha=4.1× 10^{-5}$, near ${T_{\rm c}}$, which is significantly lower than its previously measured value near zero temperature.

• Reweighting the quark Sivers function with STAR jet data

  Carlo Flore, Maria Elena Boglione, Umberto D'Alesio, Josè Osvaldo Gonzalez-Hernandez, Francesco Murgia, Alexei Prokudin

  SciPost Phys. Proc. 8, 034 (2022) · published 11 July 2022 | Toggle abstract · pdf

  The Bayesian reweighting procedure is applied for the first time to a TMD distribution, the quark Sivers function extracted from SIDIS data. By exploiting the recent published single spin asymmetry data for the inclusive jet production in $p^\uparrow p$ collisions from the STAR collaboration at RHIC, we show how such a procedure allows to incorporate the information contained in the new data set, without the need of re-fitting, and to explore a much wider $x$ region compared to SIDIS measurements. The reweighting method is also extended to the case of asymmetric errors, and the results show a significant improvement on the knowledge of the quark Sivers function.

• Sivers extraction with Neural Network

  I. P. Fernando, N. Newton, D. Seay, D. Keller

  SciPost Phys. Proc. 8, 035 (2022) · published 11 July 2022 | Toggle abstract · pdf

  Psuedo-data with simulated experimental errors can be generated to train an ensemble of Artificial Neural Networks (ANN) implemented on a regression to extract Transverse Momentum-dependent Distributions (TMDs). A preliminary analysis is presented on the reliability in extraction of the Sivers function imposed in the pseudo-data given the bounds on the experimental errors, data sparsity, and complexity of phase-space.