Publications

Order by: publication date number of citations

• Constraints on beta functions in field theories

  Han Ma, Sung-Sik Lee

  SciPost Phys. 12, 046 (2022) · published 1 February 2022 | Toggle abstract · pdf

  The $\beta$-functions describe how couplings run under the renormalization group flow in field theories. In general, all couplings that respect the symmetry and locality are generated under the renormalization group flow, and the exact renormalization group flow is characterized by the $\beta$-functions defined in the infinite dimensional space of couplings. In this paper, we show that the renormalization group flow is highly constrained so that the $\beta$-functions defined in a measure zero subspace of couplings completely determine the $\beta$-functions in the entire space of couplings. We provide a quantum renormalization group-based algorithm for reconstructing the full $\beta$-functions from the $\beta$-functions defined in the subspace. As examples, we derive the full $\beta$-functions for the $O(N)$ vector model and the $O_L(N) \times O_R(N)$ matrix model entirely from the $\beta$-functions defined in the subspace of single-trace couplings.

  2 citations

• High-dimensional and permutation invariant anomaly detection

  Vinicius Mikuni, Benjamin Nachman

  SciPost Phys. 16, 062 (2024) · published 29 February 2024 | Toggle abstract · pdf

  Methods for anomaly detection of new physics processes are often limited to low-dimensional spaces due to the difficulty of learning high-dimensional probability densities. Particularly at the constituent level, incorporating desirable properties such as permutation invariance and variable-length inputs becomes difficult within popular density estimation methods. In this work, we introduce a permutation-invariant density estimator for particle physics data based on diffusion models, specifically designed to handle variable-length inputs. We demonstrate the efficacy of our methodology by utilizing the learned density as a permutation-invariant anomaly detection score, effectively identifying jets with low likelihood under the background-only hypothesis. To validate our density estimation method, we investigate the ratio of learned densities and compare to those obtained by a supervised classification algorithm.

  2 citations

• Engineering Gaussian states of light from a planar microcavity

  Mathias Van Regemortel, Sylvain Ravets, Atac Imamoglu, Iacopo Carusotto, Michiel Wouters

  SciPost Phys. 5, 013 (2018) · published 30 July 2018 | Toggle abstract · pdf

  Quantum fluids of light in a nonlinear planar microcavity can exhibit antibunched photon statistics at short distances due to repulsive polariton interactions. We show that, despite the weakness of the nonlinearity, the antibunching signal can be amplified orders of magnitude with an appropriate free-space optics scheme to select and interfere output modes. Our results are understood from the unconventional photon blockade perspective by analyzing the approximate Gaussian output state of the microcavity. In a second part, we illustrate how the temporal and spatial profile of the density-density correlation function of a fluid of light can be reconstructed with free-space optics. Also here the nontrivial (anti)bunching signal can be amplified significantly by shaping the light emitted by the microcavity.

  2 citations

• First steps towards the reconstruction of the squark flavour structure

  Jordan Bernigaud, Björn Herrmann

  SciPost Phys. 6, 066 (2019) · published 11 June 2019 | Toggle abstract · pdf

  Assuming the observation of a squark at the Large Hadron Collider, we investigate methods to access its flavour content and thus gain information on the underlying flavour structure of the theory. Based on simple observables, we apply a likelihood inference method to determine the top-flavour content of the observed particle. In addition, we employ a multivariate analysis in order to classify different flavour hypotheses. Both methods are discussed within a simplified model and the more general Minimal Supersymmetric Standard Model including most general squark mixing. We conclude that the likelihood inference may provide an estimation of the top-flavour content if additional knowledge, especially on the gaugino sector is available, while the multivariate analysis identifies different flavour patterns and can accommodate a more minimalistic set of observables.

  2 citations

• Chaotic correlation functions with complex fermions

  Ritabrata Bhattacharya, Dileep P. Jatkar, Arnab Kundu

  SciPost Phys. Core 4, 018 (2021) · published 9 June 2021 | Toggle abstract · pdf

  We study correlation functions in the complex fermion SYK model. We focus, specifically, on the h = 2 mode which explicitly breaks conformal invariance and exhibits the chaotic behaviour. We explicitly compute fermion six-point function and extract the corresponding six-point OTOC which exhibits an exponential growth with maximal chaos. Following the program of Gross-Rosenhaus, this correlator contains information of the bulk cubic coupling, at the conformal point as well as perturbatively away from it. Unlike the conformal modes with high values of h, the h = 2 mode has contact interaction dominating over the planar in the large q limit.

  2 citations

• Gauging tensor networks with belief propagation

  Joseph Tindall, Matt Fishman

  SciPost Phys. 15, 222 (2023) · published 1 December 2023 | Toggle abstract · pdf

  Effectively compressing and optimizing tensor networks requires reliable methods for fixing the latent degrees of freedom of the tensors, known as the gauge. Here we introduce a new algorithm for gauging tensor networks using belief propagation, a method that was originally formulated for performing statistical inference on graphical models and has recently found applications in tensor network algorithms. We show that this method is closely related to known tensor network gauging methods. It has the practical advantage, however, that existing belief propagation implementations can be repurposed for tensor network gauging, and that belief propagation is a very simple algorithm based on just tensor contractions so it can be easier to implement, optimize, and generalize. We present numerical evidence and scaling arguments that this algorithm is faster than existing gauging algorithms, demonstrating its usage on structured, unstructured, and infinite tensor networks. Additionally, we apply this method to improve the accuracy of the widely used simple update gate evolution algorithm.

  2 citations

• Quantum criticality in many-body parafermion chains

  Ville Lahtinen, Teresia Mansson, Eddy Ardonne

  SciPost Phys. Core 4, 014 (2021) · published 28 May 2021 | Toggle abstract · pdf

  We construct local generalizations of 3-state Potts models with exotic critical points. We analytically show that these are described by non-diagonal modular invariant partition functions of products of $Z_3$ parafermion or $u(1)_6$ conformal field theories (CFTs). These correspond either to non-trivial permutation invariants or block diagonal invariants, that one can understand in terms of anyon condensation. In terms of lattice parafermion operators, the constructed models correspond to parafermion chains with many-body terms. Our construction is based on how the partition function of a CFT depends on symmetry sectors and boundary conditions. This enables to write the partition function corresponding to one modular invariant as a linear combination of another over different sectors and boundary conditions, which translates to a general recipe how to write down a microscopic model, tuned to criticality. We show that the scheme can also be extended to construct critical generalizations of $k$-state clock type models.

  2 citations

• Coarse-grained curvature tensor on polygonal surfaces

  Charlie Duclut, Aboutaleb Amiri, Joris Paijmans, Frank Jülicher

  SciPost Phys. Core 5, 011 (2022) · published 11 March 2022 | Toggle abstract · pdf

  Using concepts from integral geometry, we propose a definition for a local coarse-grained curvature tensor that is well-defined on polygonal surfaces. This coarse-grained curvature tensor shows fast convergence to the curvature tensor of smooth surfaces, capturing with accuracy not only the principal curvatures but also the principal directions of curvature. Thanks to the additivity of the integrated curvature tensor, coarse-graining procedures can be implemented to compute it over arbitrary patches of polygons. When computed for a closed surface, the integrated curvature tensor is identical to a rank-2 Minkowski tensor. We also provide an algorithm to extend an existing C++ package, that can be used to compute efficiently local curvature tensors on triangulated surfaces.

  2 citations

• Associative bond swaps in molecular dynamics

  Simone Ciarella, Wouter G. Ellenbroek

  SciPost Phys. 12, 128 (2022) · published 12 April 2022 | Toggle abstract · pdf

  We implement a three-body potential to model associative bond swaps, and release it as part of the HOOMD-blue software. The use of a three-body potential to model swaps has been proven to be effective and has recently provided useful insights into the mechanics and dynamics of adaptive network materials such as vitrimers. It is elegant because it can be used in plain molecular dynamics simulations without the need for topology-altering Monte Carlo steps, and naturally represents typical physical features such as slip-bond behavior. It is easily tunable with a single parameter to control the average swap rate. Here, we show how associative bond swaps can be used to speed up the equilibration of systems that self-assemble by avoiding traps and pitfalls, corresponding to long-lived metastable configurations. Our results demonstrate the possibilities of these swaps not only for modeling systems that are associative by nature, but also for increasing simulation efficiency in other systems that are modellable in HOOMD-blue.

  2 citations

• Shallow water memory: Stokes and Darwin drifts

  M. M. Sheikh-Jabbari, V. Taghiloo, M. H. Vahidinia

  SciPost Phys. 15, 115 (2023) · published 26 September 2023 | Toggle abstract · pdf

  It has been shown in [SciPost Phys. 14, 102 (2023)] that shallow water in the Euler description admits a dual gauge theory formulation. We show in the Lagrange description this gauge symmetry is a manifestation of the 2 dimensional area-preserving diffeomorphisms. We find surface charges associated with the gauge symmetry and their algebra, and study their physics in the shallow water system. In particular, we provide a reinterpretation of the Kelvin circulation theorem in terms of conserved charges. In the linear shallow water case, the charges form a u(1) current algebra with level proportional to the Coriolis parameter over the height of the fluid. We also study memory effect for the gauge theory description of the linearized shallow water and show Euler, Stokes and Darwin drifts can be understood as a memory effect and/or change of the surface charges in the gauge theory description.

  2 citations