Publications

Order by: publication date number of citations

• Non-standard neutrino spectra from annihilating neutralino dark matter

  Melissa van Beekveld, Wim Beenakker, Sascha Caron, Jochem Kip, Roberto Ruiz de Austri, Zhongyi Zhang

  SciPost Phys. Core 6, 006 (2023) · published 7 February 2023 | Toggle abstract · pdf

  Neutrino telescope experiments are rapidly becoming more competitive in indirect detection searches for dark matter. Neutrino signals arising from dark matter annihilations are typically assumed to originate from the hadronisation and decay of Standard Model particles. Here we showcase a supersymmetric model, the BLSSMIS, that can simultaneously obey current experimental limits while still providing a potentially observable non-standard neutrino spectrum from dark matter annihilation.

  1 citation

• Learning Summary Statistics for Bayesian Inference with Autoencoders

  Carlo Albert, Simone Ulzega, Firat Ozdemir, Fernando Perez-Cruz, Antonietta Mira

  SciPost Phys. Core 5, 043 (2022) · published 1 September 2022 | Toggle abstract · pdf

  For stochastic models with intractable likelihood functions, approximate Bayesian computation offers a way of approximating the true posterior through repeated comparisons of observations with simulated model outputs in terms of a small set of summary statistics. These statistics need to retain the information that is relevant for constraining the parameters but cancel out the noise. They can thus be seen as thermodynamic state variables, for general stochastic models. For many scientific applications, we need strictly more summary statistics than model parameters to reach a satisfactory approximation of the posterior. Therefore, we propose to use the inner dimension of deep neural network based Autoencoders as summary statistics. To create an incentive for the encoder to encode all the parameter-related information but not the noise, we give the decoder access to explicit or implicit information on the noise that has been used to generate the training data. We validate the approach empirically on two types of stochastic models.

  1 citation

• Monopole harmonics on $\mathbb{CP}^{n-1}$

  Dmitri Bykov, Andrei Smilga

  SciPost Phys. 15, 195 (2023) · published 14 November 2023 | Toggle abstract · pdf

  We find the spectra and eigenfunctions of both ordinary and supersymmetric quantum-mechanical models describing the motion of a charged particle over the $\mathbb{CP}^{n-1}$ manifold in the presence of a background monopole-like gauge field. The states form degenerate $SU(n)$ multiplets and their wave functions acquire a very simple form being expressed via homogeneous coordinates. Their relationship to multidimensional orthogonal polynomials of a special kind is discussed. By the well-known isomorphism between the twisted Dolbeault and Dirac complexes, our construction also gives the eigenfunctions and eigenvalues of the Dirac operator on complex projective spaces in a monopole background.

  1 citation

• Invariant approach to the driven Jaynes-Cummings model

  Ivan Alejandro Bocanegra-Garay, L. Hernández-Sánchez, Irán Ramos-Prieto, Francisco Soto-Eguibar, Héctor Manuel Moya-Cessa

  SciPost Phys. 16, 007 (2024) · published 8 January 2024 | Toggle abstract · pdf

  We investigate the dynamics of the driven Jaynes-Cummings model, where a two-level atom interacts with a quantized field and both, atom and field, are driven by an external classical field. Via an invariant approach, we are able to transform the corresponding Hamiltonian into the one of the standard Jaynes-Cummings model. Subsequently, the exact analytical solution of the Schrödinger equation for the driven system is obtained and employed to analyze some of its dynamical variables.

  1 citation

• Probing fractional statistics in quantum simulators of spin liquid Hamiltonians

  Shiyu Zhou, Maria Zelenayova, Oliver Hart, Claudio Chamon, Claudio Castelnovo

  SciPost Phys. 15, 194 (2023) · published 14 November 2023 | Toggle abstract · pdf

  Recent advances in programmable quantum devices brought to the fore the intriguing possibility of using them to realise and investigate topological quantum spin liquid phases. This new and exciting direction brings about important research questions on how to probe and determine the presence of such exotic, highly entangled phases in a noisy quantum environment. One of the most promising tools is investigating the behaviour of the topological excitations, and in particular their fractional statistics. In this work we put forward a generic route to achieve this, and we illustrate it in the specific case of $\mathbb{Z}_2$ topological spin liquids implemented with the aid of combinatorial gauge symmetry. We design a convenient architecture to study signatures of fractional statistics via quasiparticle interferometry, and we assess its robustness to diagonal and off-diagonal disorder, as well as to dephasing - effects that are generally pervasive in current quantum programmable devices. Interestingly, when turned on its head, our scheme provides a remarkably clear test of the "quantumness" of these devices, with robust signatures that crucially hinge on quantum coherence and quantum interference effects, and cannot be mimicked by classical stochastic processes.

  1 citation

• Surface-acoustic-wave-induced unconventional superconducting pairing

  Viktoriia Kornich

  SciPost Phys. Core 5, 005 (2022) · published 27 January 2022 | Toggle abstract · pdf

  Unconventional superconductivity is usually associated with symmetry breaking in the system. Here we consider a simple setup consisting of a solid state material with conduction electrons and an applied surface acoustic wave (SAW), that can break time and spatial translation symmetries. We study the symmetries of the possible SAW-induced order parameters, showing that even-frequency spin-triplet odd-parity order parameter can occur. We suggest different methods of how to engineer the symmetries of the order parameters using SAWs and the applications of such setups.

  1 citation

• Controlling superfluid flows using dissipative impurities

  Martin Will , Jamir Marino, Herwig Ott, Michael Fleischhauer

  SciPost Phys. 14, 064 (2023) · published 6 April 2023 | Toggle abstract · pdf

  We propose and analyze a protocol to create and control the superfluid flow in a one dimensional, weakly interacting Bose gas by noisy point contacts. Considering first a single contact in a static or moving condensate, we identify three different dynamical regimes: I. a linear response regime, where the noise induces a coherent flow in proportion to the strength of the noise, II. a Zeno regime with suppressed currents, and III. a regime of continuous soliton emission. Generalizing to two point contacts in a condensate at rest we show that noise tuning can be employed to control or stabilize the superfluid transport of particles along the segment which connects them.

  1 citation

• Codebase release 0.5 for divERGe

  Jonas B. Profe, Dante M. Kennes, Lennart Klebl

  SciPost Phys. Codebases 26-r0.5 (2024) · published 8 February 2024 | Toggle abstract · src

  We present divERGe, an open source, high-performance C/C++/Python library for functional renormalization group (FRG) calculations on lattice fermions. The versatile model interface is tailored to real materials applications and seamlessly integrates with existing, standard tools from the ab-initio community. The code fully supports multi-site, multi-orbital, and non-SU(2) models in all of the three included FRG variants: TU$^2$FRG, N-patch FRG, and grid FRG. With this, the divERGe library paves the way for widespread application of FRG as a tool in the study of competing orders in quantum materials.

  1 citation

• Sensitivity of a collisional single-atom spin probe

  Jens Nettersheim, Quentin Bouton, Daniel Adam, Artur Widera

  SciPost Phys. Core 6, 009 (2023) · published 16 February 2023 | Toggle abstract · pdf

  We study the sensitivity of a collisional single-atom probe for ultracold gases. Inelastic spin-exchange collisions map information about the gas temperature $T$ or external magnetic field $B$ onto the quantum spin-population of single-atom probes, and previous work showed enhanced sensitivity for short-time nonequilibrium spin dynamics [Phys. Rev. X 10, 011018 (2020)]. Here, we numerically investigate the steady-state sensitivity of such single-atom probes to various observables. We find that the probe shows distinct sensitivity maxima in the ($B,T$) parameter diagram, although the underlying spin-exchange rates scale monotonically with temperature and magnetic field. In parameter space, the probe generally has the largest sensitivity when sensing the energy ratio between thermal energy and Zeeman energy in an externally applied magnetic field, while the sensitivity to the absolute energy, i.e., the sum of kinetic and Zeeman energy, is low. We identify the parameters yielding sensitivity maxima for a given absolute energy, which we can relate to a direct comparison of the thermal Maxwell-Boltzmann distribution with the Zeeman-energy splitting. We compare our equilibrium results to nonequilibrium experimental results from a single-atom quantum probe, showing that the sensitivity maxima in parameter space qualitatively prevail also in the nonequilibrium dynamics, while a quantitative difference remains. Our work thereby offers a microscopic explanation for the properties and performance of this single-atom quantum probe, connecting thermodynamic properties to microscopic interaction mechanisms. Our results pave the way for optimization of quantum-probe applications in ($B,T$) parameter space beyond the previously shown boost by nonequilibrium dynamics.

  1 citation

• Automatic transformation of irreducible representations for efficient contraction of tensors with cyclic group symmetry

  Yang Gao, Phillip Helms, Garnet Kin-Lic Chan, Edgar Solomonik

  SciPost Phys. Codebases 10 (2023) · published 24 February 2023 | Toggle abstract · pdf

  Tensor contractions are ubiquitous in computational chemistry and physics, where tensors generally represent states or operators and contractions express the algebra of these quantities. In this context, the states and operators often preserve physical conservation laws, which are manifested as group symmetries in the tensors. These group symmetries imply that each tensor has block sparsity and can be stored in a reduced form. For nontrivial contractions, the memory footprint and cost are lowered, respectively, by a linear and a quadratic factor in the number of symmetry sectors. State-of-the-art tensor contraction software libraries exploit this opportunity by iterating over blocks or using general block-sparse tensor representations. Both approaches entail overhead in performance and code complexity. With intuition aided by tensor diagrams, we present a technique, irreducible representation alignment, which enables efficient handling of Abelian group symmetries via only dense tensors, by using contraction-specific reduced forms. This technique yields a general algorithm for arbitrary group symmetric contractions, which we implement in Python and apply to a variety of representative contractions from quantum chemistry and tensor network methods. As a consequence of relying on only dense tensor contractions, we can easily make use of efficient batched matrix multiplication via Intel's MKL and distributed tensor contraction via the Cyclops library, achieving good efficiency and parallel scalability on up to 4096 Knights Landing cores of a supercomputer.

  1 citation