Publications

Order by: publication date number of citations

• Magnetic properties of the putative higher-order topological insulator EuIn$_2$As$_2$

  Tomasz Toliński, Dariusz Kaczorowski

  SciPost Phys. Proc. 11, 005 (2023) · published 5 June 2023 | Toggle abstract · pdf

  In higher-order topological insulator (HOTI), a gap is preserved both for the bulk and the surface states, and only hinges or corners become gapless. Recently, it has been predicted that the antiferromagnetic compound EuIn$_2$As$_2$ can host both the HOTI and axion insulator features. Preliminary experimental confirmation of this finding was obtained using angle-resolved photoemission spectroscopy. The main objective of this work was to characterize the anisotropic magnetic properties of single-crystalline EuIn$_2$As$_2$. In addition, complementary studies on the transport properties, heat capacity, and magnetocaloric effect in this compound were performed.

  3 citations

• A testable theory for high-Tc superconductivity in cuprates

  Eduardo C. Marino

  SciPost Phys. Proc. 11, 004 (2023) · published 5 June 2023 | Toggle abstract · pdf

  A number of theories for the superconductivity in cuprates, have been proposed in the more than 30 years that have elapsed since its discovery. A common feature of these theories is the small number, or even the absence, of quantitative predictions that could be compared to a vast number of experimental data, which are, conversely, available. Such theories are, consequently non-testable. We describe the foundations and a number of applications of a theory describing High-Tc Superconductivity in cuprates, which we proposed recently, that besides being testable, has proven to meet successfully the tests to which it has been submitted so far.

• Efficient scheme for time-dependent thermal pure quantum state: Application to the Kitaev model with armchair edges

  Hirokazu Taguchi, Akihisa Koga, Yuta Murakami

  SciPost Phys. Proc. 11, 003 (2023) · published 5 June 2023 | Toggle abstract · pdf

  We consider the time-dependent thermal pure quantum state method and introduce the efficient scheme to evaluate the change in physical quantities induced by the time-dependent perturbations, which has been proposed in our previous paper [H. Taguchi et al., Phys. Rev. B 105, 125137 (2022)]. Here, we treat the Kitaev model to consider the Majorana-mediated spin transport, as an example. We demonstrate how efficient our scheme is to evaluate spin oscillations induced by the magnetic field pulse.

• Single crystal growth of PrNiGe$_2$ compounds

  Kousei Ishiwatari, Kaito Hoshii, Keisuke Ida, Masashi Ohashi

  SciPost Phys. Proc. 11, 002 (2023) · published 5 June 2023 | Toggle abstract · pdf

  We report on the magnetic characterization of a praseodym intermetallic PrNiGe$_2$. Several single crystals are grown by the Czochralski method from Ni- deficient sample as the initial one. X-ray analysis of PrNi$_{0.8}$Ge$_2$ indicated the CeNiSi$_2$-type structure as the only phase. The magnetic measurements clearly indicate that PrNi$_x$Ge$_2$ exhibits a ferromagnetic orderings at 12 K, which is independent with of composition of Ni. A strong anisotropy along the three principal crystallographic directions was observed, reflecting the orthorhombic symmetry of the crystal structure. The $b$-axis was found to be the easy axis of magnetization.

• Quantum spin nematic liquid in the low-dimensional anisotropic magnets -S=1/2 delta spin chain with the anisotropic ferromagnetic interaction in magnetic field-

  Toru Sakai, Rito Furuchi, Hiroki Nakano, Kiyomi Okamoto

  SciPost Phys. Proc. 11, 001 (2023) · published 5 June 2023 | Toggle abstract · pdf

  The magnetization process of the $S=1/2$ delta chain with the anisotropic ferromagnetic interaction is investigated using the numerical diagonalization of finite-size clusters. It is found that the spin nematic liquid phase appears in higher magnetization region, as well as the SDW liquid one in lower region.

• Residual matrix product state for machine learning

  Ye-Ming Meng, Jing Zhang, Peng Zhang, Chao Gao, Shi-Ju Ran

  SciPost Phys. 14, 142 (2023) · published 2 June 2023 | Toggle abstract · pdf

  Tensor network, which originates from quantum physics, is emerging as an efficient tool for classical and quantum machine learning. Nevertheless, there still exists a considerable accuracy gap between tensor network and the sophisticated neural network models for classical machine learning. In this work, we combine the ideas of matrix product state (MPS), the simplest tensor network structure, and residual neural network and propose the residual matrix product state (ResMPS). The ResMPS can be treated as a network where its layers map the "hidden" features to the outputs (e.g., classifications), and the variational parameters of the layers are the functions of the features of the samples (e.g., pixels of images). This is different from neural network, where the layers map feed-forwardly the features to the output. The ResMPS can equip with the non-linear activations and dropout layers, and outperforms the state-of-the-art tensor network models in terms of efficiency, stability, and expression power. Besides, ResMPS is interpretable from the perspective of polynomial expansion, where the factorization and exponential machines naturally emerge. Our work contributes to connecting and hybridizing neural and tensor networks, which is crucial to further enhance our understanding of the working mechanisms and improve the performance of both models.

  2 citations

• Knots and entanglement

  Jin-Long Huang, John McGreevy, Bowen Shi

  SciPost Phys. 14, 141 (2023) · published 2 June 2023 | Toggle abstract · pdf

  We extend the entanglement bootstrap program to (3+1)-dimensions. We study knotted excitations of (3+1)-dimensional liquid topological orders and exotic fusion processes of loops. As in previous work in (2+1)-dimensions [Ann. Phys. 418, 168164 (2020), Phys. Rev. B 103, 115150 (2021)], we define a variety of superselection sectors and fusion spaces from two axioms on the ground state entanglement entropy. In particular, we identify fusion spaces associated with knots. We generalize the information convex set to a new class of regions called immersed regions, promoting various theorems to this new context. Examples from solvable models are provided; for instance, a concrete calculation of knot multiplicity shows that the knot complement of a trefoil knot can store quantum information. We define spiral maps that allow us to understand consistency relations for torus knots as well as spiral fusions of fluxes.

  1 citation

• Fragmentation-induced localization and boundary charges in dimensions two and above

  Julius Lehmann, Pablo Sala de Torres-Solanot, Frank Pollmann, Tibor Rakovszky

  SciPost Phys. 14, 140 (2023) · published 1 June 2023 | Toggle abstract · pdf

  We study higher dimensional models with symmetric correlated hoppings, which generalize a one-dimensional model introduced in the context of dipole-conserving dynamics. We prove rigorously that whenever the local configuration space takes its smallest non-trivial value, these models exhibit localized behavior due to fragmentation, in any dimension. For the same class of models, we then construct a hierarchy of conserved quantities that are power-law localized at the boundary of the system with increasing powers. Combining these with Mazur's bound, we prove that boundary correlations are infinitely long lived, even when the bulk is not localized. We use our results to construct quantum Hamiltonians that exhibit the analogues of strong zero modes in two and higher dimensions.

  6 citations

• Static and dynamical signatures of Dzyaloshinskii-Moriya interactions in the Heisenberg model on the kagome lattice

  Francesco Ferrari, Sen Niu, Juraj Hasik, Yasir Iqbal, Didier Poilblanc, Federico Becca

  SciPost Phys. 14, 139 (2023) · published 1 June 2023 | Toggle abstract · pdf

  Motivated by recent experiments on Cs$_2$Cu$_3$SnF$_{12}$ and YCu$_{3}$(OH)$_{6}$Cl$_{3}$, we consider the ${S=1/2}$ Heisenberg model on the kagome lattice with nearest-neighbor super-exchange $J$ and (out-of-plane) Dzyaloshinskii-Moriya interaction $J_D$, which favors (in-plane) ${{\bf Q}=(0,0)}$ magnetic order. By using both variational Monte Carlo and tensor-network approaches, we show that the ground state develops a finite magnetization for $J_D/J \gtrsim 0.03 \mathrm{-} 0.04$; instead, for smaller values of the Dzyaloshinskii-Moriya interaction, the ground state has no magnetic order and, according to the fermionic wave function, develops a gap in the spinon spectrum, which vanishes for $J_D \to 0$. The small value of $J_D/J$ for the onset of magnetic order is particularly relevant for the interpretation of low-temperature behaviors of kagome antiferromagnets, including ZnCu$_{3}$(OH)$_{6}$Cl$_{2}$. For this reason, we assess the spin dynamical structure factor and the corresponding low-energy spectrum, by using the variational Monte Carlo technique. The existence of a continuum of excitations above the magnon modes is observed within the magnetically ordered phase, with a broad peak above the lowest-energy magnons, similarly to what has been detected by inelastic neutron scattering on Cs$_{2}$Cu$_{3}$SnF$_{12}$.

  11 citations

• STEP: A tool to perform tests of smoothness on differential distributions based on expansion of polynomials

  Patrick L. S. Connor, Radek Žlebčík

  SciPost Phys. Core 6, 040 (2023) · published 1 June 2023 | Toggle abstract · pdf

  We motivate and describe a method based on fits with polynomials to test the smoothness of differential distributions. As a demonstration, we apply the method to several measurements of inclusive jet double-differential cross section in the jet transverse momentum and rapidity at the Tevatron and LHC. This method opens new possibilities to test the quality of differential distributions used for the extraction of physics quantities such as the strong coupling.