arXiv subjects

Carsten Honerkamp

Publications and source records attributed to Carsten Honerkamp.

At least 19 recordsLinked to original sources

arXiv2025

Chiral topological superconductivity in hole-doped Sn/Si(111)

A third monolayer of tin atoms on the semiconductor substrate Si(111) has been shown to become superconducting upon six to ten percent hole doping. Experiments have reported promising results hinting at a superconducting chiral $d$-wave order parameter. Here we examine Sn/Si(111) by combining most recent ab initio results, quasi-particle interference calculations, state-of-the-art truncated-unity functional renormalization group simulations and Bogoliubov-de Gennes analysis. We show remarkable agreement between experimental and theoretical quasi-particle interference data both in the metallic and superconducting regimes. The interacting phase diagram reveals that the superconductivity is indeed chiral $d$-wave with Chern number $C=4$. Surprisingly, magnetically ordered phases are absent, instead we find charge density wave order, as observed in related compounds, as a competing phase. Our results demonstrate that Sn/Si(111) is an outstanding candidate material for chiral topological superconductivity.

cond-mat.supr-con↗

arXiv2024

Chern number landscape of spin-orbit coupled chiral superconductors

Chiral superconductors are one of the predominant quantum electronic states of matter where topology, symmetry, and Fermiology intertwine. This is pushed to a new limit by further invoking the coupling between spin and charge degrees of freedom, which fundamentally affects the principal nature of the Cooper pair wave function. We investigate the onset of superconductivity in the Rashba-Hubbard model on the triangular lattice, which is symmetry-classified by the associated irreducible representations (irrep) of the hexagonal point group. From an instability analysis by means of the truncated-unity functional renormalization group (TU-FRG) we find the $E_2$ irrep to dominate a large fraction of phase space and to lead up to an energetically preferred gapped, chiral superconducting state. The topological phase space classification associated with the anomalous propagators obtained from TU-FRG reveals a fragmentation of the $E_2$ domain into different topological sectors with vastly differing Chern numbers. It hints at a potentially applicable high sensitivity and tunability of chiral superconductors with respect to topological edge modes and phase transitions.

cond-mat.str-el↗

arXiv2023

Spurious self-feedback of mean-field predictions inflates infection curves

The susceptible-infected-recovered (SIR) model and its variants form the foundation of our understanding of the spread of diseases. Here, each agent can be in one of three states (susceptible, infected, or recovered), and transitions between these states follow a stochastic process. The probability of an agent becoming infected depends on the number of its infected neighbors, hence all agents are correlated. A common mean-field theory of the same stochastic process however, assumes that the agents are statistically independent. This leads to a self-feedback effect in the approximation: when an agent infects its neighbors, this infection may subsequently travel back to the original agent at a later time, leading to a self-infection of the agent which is not present in the underlying stochastic process. We here compute the first order correction to the mean-field assumption, which takes fluctuations up to second order in the interaction strength into account. We find that it cancels the self-feedback effect, leading to smaller infection rates. In the SIR model and in the SIRS model, the correction significantly improves predictions. In particular, it captures how sparsity dampens the spread of the disease: this indicates that reducing the number of contacts is more effective than predicted by mean-field models.

cond-mat.dis-nn↗

arXiv2023

Learning Interacting Theories from Data

One challenge of physics is to explain how collective properties arise from microscopic interactions. Indeed, interactions form the building blocks of almost all physical theories and are described by polynomial terms in the action. The traditional approach is to derive these terms from elementary processes and then use the resulting model to make predictions for the entire system. But what if the underlying processes are unknown? Can we reverse the approach and learn the microscopic action by observing the entire system? We use invertible neural networks (INNs) to first learn the observed data distribution. By the choice of a suitable nonlinearity for the neuronal activation function, we are then able to compute the action from the weights of the trained model; a diagrammatic language expresses the change of the action from layer to layer. This process uncovers how the network hierarchically constructs interactions via nonlinear transformations of pairwise relations. We test this approach on simulated data sets of interacting theories. The network consistently reproduces a broad class of unimodal distributions; outside this class, it finds effective theories that approximate the data statistics up to the third cumulant. We explicitly show how network depth and data quantity jointly improve the agreement between the learned and the true model. This work shows how to leverage the power of machine learning to transparently extract microscopic models from data.

cond-mat.dis-nn↗

arXiv2022

Rashba spin-orbit coupling in the square lattice Hubbard model: A truncated-unity functional renormalization group study

The Rashba-Hubbard model on the square lattice is the paradigmatic case for studying the effect of spin-orbit coupling, which breaks spin and inversion symmetry, in a correlated electron system. We employ a truncated-unity variant of the functional renormalization group which allows us to analyze magnetic and superconducting instabilities on equal footing. We derive phase diagrams depending on the strengths of Rasbha spin-orbit coupling, real second-neighbor hopping and electron filling. We find commensurate and incommensurate magnetic phases which compete with d-wave superconductivity. Due to the breaking of inversion symmetry, singlet and triplet components mix; we quantify the mixing of d-wave singlet pairing with f-wave triplet pairing.

cond-mat.str-el↗

arXiv2022

Understanding the three-dimensional quantum Hall effect in generic multi-Weyl semimetals

The quantum Hall effect in three-dimensional Weyl semimetal (WSM) receives significant attention for the emergence of the Fermi loop where the underlying two-dimensional Hall conductivity, namely, sheet Hall conductivity, shows quantized plateaus. Considering the tilted lattice models for multi Weyl semimetals (mWSMs), we systematically study the Landau levels (LLs) and magneto-Hall conductivity in the presence of parallel and perpendicular (with respect to the Weyl node's separation) magnetic field, i.e., $\mathbf{ B}\parallel z$ and $\mathbf{B}\parallel x$, to explore the impact of tilting and non-linearity in the dispersion. We make use of two (single) node low-energy models to qualitatively explain the emergence of mid-gap chiral (linear crossing of chiral) LLs on the lattice for $\mathbf{ B}\parallel z$ ($\mathbf{ B}\parallel x$). Remarkably, we find that the sheet Hall conductivity becomes quantized for $\mathbf{ B}\parallel z$ even when two Weyl nodes project onto a single Fermi point in two opposite surfaces, forming a Fermi loop with $k_z$ as the good quantum number. On the other hand, the Fermi loop, connecting two distinct Fermi points in two opposite surfaces, with $k_x$ being the good quantum number, causes the quantization in sheet Hall conductivity for $\mathbf{ B}\parallel x$. The quantization is almost lost (perfectly remained) in the type-II phase for $\mathbf{ B}\parallel x$ ($\mathbf{ B}\parallel z$). Interestingly, the jump profiles between the adjacent quantized plateaus change with the topological charge for both of the above cases. The momentum-integrated three-dimensional Hall conductivity is not quantized; however, it bears the signature of chiral LLs as resulting in the linear dependence on $μ$ for small $μ$. The linear zone (its slope) reduces (increases) as the tilt (topological charge) of the underlying WSM increases.

cond-mat.mes-hall↗

arXiv2022

Self-consistent formulations for stochastic nonlinear neuronal dynamics

Neural dynamics is often investigated with tools from bifurcation theory. However, many neuron models are stochastic, mimicking fluctuations in the input from unknown parts of the brain or the spiking nature of signals. Noise changes the dynamics with respect to the deterministic model; in particular bifurcation theory cannot be applied. We formulate stochastic neuronal dynamics in the Martin-Siggia-Rose de Dominicis-Janssen (MSRDJ) formalism and present the fluctuation expansion of the effective action and the functional renormalization group (fRG) as two systematic ways to incorporate corrections to the mean dynamics and time-dependent statistics due to fluctuations in the presence of nonlinear neuronal gain. To formulate self-consistency equations, we derive a fundamental link between the effective action in the Onsager-Machlup(OM) formalism, which allows the study of phase transitions, and the MSRDJ effective action, which is computationally advantageous. These results in particular allow the derivation of an OM effective action for systems with non-Gaussian noise. This approach naturally leads to effective deterministic equations for the first moment of the stochastic system; they explain how nonlinearities and noise cooperate to produce memory effects. Moreover, the MSRDJ formulation yields an effective linear system that has identical power spectra and linear response. Starting from the better known loopwise approximation, we then discuss the use of the fRG as a method to obtain self-consistency beyond the mean. We present a new efficient truncation scheme for the hierarchy of flow equations for the vertex functions by adapting the Blaizot, Méndez and Wschebor approximation from the derivative expansion to the vertex expansion. The methods are presented by means of the simplest possible example of a stochastic differential equation that has generic features of neuronal dynamics.

cond-mat.stat-mech↗

arXiv2021

Magnetic ordering tendencies in hexagonal boron nitride-bilayer graphene moiré structures

When hexagonal boron nitride (hBN) and graphene are aligned at zero or small twist angle, a moiré structure is formed due to the small lattice constant mismatch between the two structures. In this work, we analyze magnetic ordering tendencies, driven by onsite Coulomb interactions, of encapsulated bilayer graphene (BG) forming a moiré structure with one (hBN-BG) or both hBN layers (hBN-BG-hBN), using the random phase approximation. The calculations are performed in a fully atomistic Hubbard model that takes into account all $π$-electrons of the carbon atoms in one moiré unit cell. We analyze the charge neutral case and find that the dominant magnetic ordering instability is uniformly antiferromagnetic. Furthermore, at low temperatures, the critical Hubbard interaction $U_c$ required to induce magnetic order is slightly larger in those systems where the moiré structure has caused a band gap opening in the non-interacting picture, although the difference is less than 6%. Mean-field calculations are employed to estimate how such an interaction-induced magnetic order may change the observable single-particle gap sizes.

cond-mat.str-el↗

arXiv2021

Global hierarchy vs. local structure: spurious self-feedback in scale-free networks

Networks with fat-tailed degree distributions are omnipresent across many scientific disciplines. Such systems are characterized by so-called hubs, specific nodes with high numbers of connections to other nodes. By this property, they are expected to be key to the collective network behavior, e.g., in Ising models on such complex topologies. This applies in particular to the transition into a globally ordered network state, which thereby proceeds in a hierarchical fashion, and with a non-trivial local structure. Standard mean-field theory of Ising models on scale-free networks underrates the presence of the hubs, while nevertheless providing remarkably reliable estimates for the onset of global order. Here, we expose that a spurious self-feedback effect, inherent to mean-field theory, underlies this apparent paradox. More specifically, we demonstrate that higher order interaction effects precisely cancel the self-feedback on the hubs, and we expose the importance of hubs for the distinct onset of local versus global order in the network. Due to the generic nature of our arguments, we expect the mechanism that we uncover for the archetypal case of Ising networks of the Barabási-Albert type to be also relevant for other systems with a strongly hierarchical underlying network structure.

cond-mat.dis-nn↗

arXiv2021

Electronic instabilities in Penrose quasi-crystals: competition, coexistence and collaboration of order

Quasicrystals lack translational symmetry, but can still exhibit long-ranged order, promoting them to candidates for unconventional physics beyond the paradigm of crystals. Here, we apply a real-space functional renormalization group approach to the prototypical quasicrystalline Penrose tiling Hubbard model treating} competing electronic instabilities in an unbiased, beyond-mean-field fashion. {\color{red} Our work reveals a delicate interplay between charge and spin degrees of freedom in quasicrystals}. Depending on the range of interactions and hopping amplitudes, we unveil a rich phase diagram including antiferromagnetic orderings, charge density waves and subleading, superconducting pairing tendencies. For certain parameter regimes we find a competition of phases, which is also common in crystals, but additionally encounter phases coexisting in a spatially separated fashion and ordering tendencies which mutually collaborate to enhance their strength. We therefore establish that quasicrystalline structures open up a route towards this rich ordering behavior uncommon to crystals and that an unbiased, beyond-mean-field approach is essential to describe this physics of quasicrystals correctly.

cond-mat.str-el↗

arXiv2021

Spin susceptibilities in magnetic type-I and type-II Weyl semimetals

We investigate interacting spin susceptibilities in lattice models for $\mathcal{T}$-reversal symmetry-broken Weyl semimetals. We employ a random phase approximation (RPA) method for the spin-SU(2)-symmetry-broken case that includes mixtures of ladder and bubble diagrams, beyond a SU(2)-symmetric case. Within this approach, the relations between the tendency towards magnetic order and the band structure tilt parameter $γ$ under different temperatures are explored. The critical interaction strength $U_c$ for magnetic ordering decreases as the tilt term changes from type-I Weyl semimetals to type-II. The lower temperature, the sharper is the drop in $U_c$ at the critical point between them. The variation of $U_c$ with a slight doping near half-filling is also studied. It is generally found that these Weyl systems show a strongly anisotropic spin response with an enhanced doubly degenerate transverse susceptibility perpendicular to tilt direction, inherited from $\mathcal{C}_{4z}$ rational symmetry of bare Hamiltonian, but with the longitudinal response suppressed with respect to that. For small tilts $γ$ and strong enough interaction, we find two degenerate ordering patterns with spin order orthogonal to the tilt direction but much shorter spin correlation length parallel to the spin direction. With increasing the tilt, the system develops instabilities with respect to in-plane magnetic orders with wavevector $(0,π, q_z)$ and $(π,0, q_z)$, with $q_z$ increasing from 0 to $π$ before the transition to a type-II Weyl semimetal is reached. These results indicate a greater richness of magnetic phases in correlated Weyl semimetals that also pose challenges for precise theoretical descriptions.

cond-mat.str-el↗

arXiv2021

Spin-fluctuation-induced pairing in twisted bilayer graphene

We investigate the interplay of magnetic fluctuations and Cooper pairing in twisted bilayer graphene from a purely microscopic model within a large-scale tight-binding approach resolving the Ångström scale. For local onsite repulsive interactions and using the random-phase approximation for spin fluctuations, we derive a microscopic effective pairing interaction that we use for self-consistent solutions of the Bogoliubov-de-Gennes equations of superconductivity. We study the predominant pairing types as function of interaction strength, temperature and band filling. For large regions of this parameter space, we find chiral $d$-wave pairing regimes, spontaneously breaking time-reversal symmetry, separated by magnetic instabilities at integer band fillings. Interestingly, the $d$-wave pairing is strongly concentrated in the AA regions of the moiré unit cell and exhibits phase windings of integer multiples of $2π$ around these superconducting islands, i.e. pinned vortices. The spontaneous circulating current creates a distinctive magnetic field pattern. This signature of the chiral pairing should be measurable by state-of-the-art experimental techniques.

cond-mat.supr-con↗

arXiv2020

Investigation of the effective interactions for the Emery model by the constrained random-phase approximation and constrained functional renormalization group

The effective interaction of downfolded low-energy models for electrons in solids can be obtained by integrating out the high energy bands away from the target band near the Fermi level. Here, we apply the constrained random-phase approximation (cRPA) and constrained functional renormalization group (cfRG), which can go beyond cRPA by including all one-loop diagrams, to calculate and compare the effective interactions of the three-band Emery model, which is often used to investigate cuprate high-temperature superconductors. At half band filling, we find that the effective interaction increases as the charge transfer energy ($Δ_{dp}$) increases and similar behavior is obtained as a function of the interatomic 2$p$-3$d$ interaction ($U_{dp}$). However, the effective interaction is more sensitive to $Δ_{dp}$ than $ U_{dp}$. For most of the parameter sets, the effective static interaction is overscreened in cRPA compared to cfRG. The low-energy models at half-filling are solved within dynamical mean-field theory (DMFT). The results show that despite the different static interactions, the systems with cRPA and cfRG interaction exhibit a Mott transition at similar values of $Δ_{dp}$. We also investigate the effective interaction as a function of doping. The cfRG effective interaction decreases as the electron number increases and displays a trend opposite to that of cRPA. Antiscreening is observed for the hole-doped case. For all the cases studied, the near-cancellation of the direct particle-hole channel is observed. This indicates that at least for the downfolding of the onsite interaction terms, methods beyond cRPA may be required.

cond-mat.str-el↗

arXiv2020

Quantitative functional renormalization-group description of the two-dimensional Hubbard model

Using a leading algorithmic implementation of the functional renormalization group (fRG) for interacting fermions on two-dimensional lattices, we provide a detailed analysis of its quantitative reliability for the Hubbard model. In particular, we show that the recently introduced multiloop extension of the fRG flow equations for the self-energy and two-particle vertex allows for a precise match with the parquet approximation also for two-dimensional lattice problems. The refinement with respect to previous fRG-based computation schemes relies on an accurate treatment of the frequency and momentum dependences of the two-particle vertex, which combines a proper inclusion of the high-frequency asymptotics with the so-called truncated unity fRG for the momentum dependence. The adoption of the latter scheme requires, as an essential step, a consistent modification of the flow equation of the self-energy. We quantitatively compare our fRG results for the self-energy and momentum-dependent susceptibilities and the corresponding solution of the parquet approximation to determinant quantum Monte Carlo data, demonstrating that the fRG is remarkably accurate up to moderate interaction strengths. The presented methodological improvements illustrate how fRG flows can be brought to a quantitative level for two-dimensional problems, providing a solid basis for the application to more general systems.

cond-mat.str-el↗

arXiv2020

Functional renormalization group for a large moiré unit cell

Layers of two-dimensional materials arranged at a twist angle with respect to each other lead to enlarged unit cells with potentially strongly altered band structures, offering a new arena for novel and engineered many-body ground states. For the exploration of these, renormalization group methods are an appropriate, flexible tool that take into account the mutual influence of competing tendencies. Here we show that, within reasonable, non-trivial approximations, the functional renormalization group known from simpler two-dimensional systems can be employed for the large-unit cell moiré superlattices with more than 10.000 bands, remedying the need to employ ad hoc restrictions to effective low-energy theories of a few bands and/or effective continuum theories. This provides a description on the atomic scale, allowing one to absorb available ab-initio information on the model parameters and therefore lending the analysis a more concrete quantitative character. For the case of twisted bilayer graphene models, we explore the leading ordering tendencies depending on the band filling and the range of interactions. The results indicate a delicate balance between distinct magnetically ordered ground states, as well as the occurrence of a charge modulation within the moiré unit cell for sufficiently non-local repulsive interaction.

cond-mat.str-el↗

arXiv2020

Pseudogap opening in the two-dimensional Hubbard model: A functional renormalization group analysis

Using the recently introduced multiloop extension of the functional renormalization group, we compute the frequency- and momentum-dependent self-energy of the two-dimensional Hubbard model at half filling and weak coupling. We show that, in the truncated-unity approach for the vertex, it is essential to adopt the Schwinger-Dyson form of the self-energy flow equation in order to capture the pseudogap opening. We provide an analytic understanding of the key role played by the flow scheme in correctly accounting for the impact of the antiferromagnetic fluctuations. For the resulting pseudogap, we present a detailed numerical analysis of its evolution with temperature, interaction strength, and loop order.

cond-mat.str-el↗

arXiv2020

Competing orders at higher-order Van Hove points

Van Hove points are special points in the energy dispersion, where the density of states exhibits analytic singularities. When a Van Hove point is close to the Fermi level, tendencies towards density wave orders, Pomeranchuk orders, and superconductivity can all be enhanced, often in more than one channel, leading to a competition between different orders and unconventional ground states. Here we consider the effects from higher-order Van Hove points, around which the dispersion is flatter than near a conventional Van Hove point, and the density of states has a power-law divergence. We argue that such points are present in intercalated graphene and other materials. We use an effective low-energy model for electrons near higher-order Van Hove points and analyze the competition between different ordering tendencies using an unbiased renormalization group approach. For purely repulsive interactions, we find that two key competitors are ferromagnetism and chiral superconductivity. For a small attractive exchange interaction, we find a new type of spin Pomeranchuk order, in which the spin order parameter winds around the Fermi surface. The supermetal state, predicted for a single higher-order Van Hove point, is an unstable fixed point in our case.

cond-mat.str-el↗

arXiv2020

A Long-Range Ising Model of a Barabási-Albert Network

Networks that have power-law connectivity, commonly referred to as the scale-free networks, are an important class of complex networks. A heterogeneous mean-field approximation has been previously proposed for the Ising model of the Barabási-Albert model of scale-free networks with classical spins on the nodes wherein it was shown that the critical temperature for such a system scales logarithmically with network size. For finite sizes, there is no criticality for such a system and hence no true phase transition in terms of singular behavior. Further, in the thermodynamic limit, the mean-field prediction of an infinite critical temperature for the system may exclude any true phase transition even then. Nevertheless, with an eye on potential applications of the model on biological systems that are generally finite, one may still try to find approximations that describe the relevant observables quantitatively. Here we present an alternative, approximate formulation for the description of the Ising model of a Barabási-Albert Network. Using the classical definition of magnetization, we show that Ising models on a network can be well-approximated by a long-range interacting homogeneous Ising model wherein each node of the network couples to all other spins with a strength determined by the mean degree of the Barabási-Albert Network. In such an effective long-range Ising model of a Barabási-Albert Network, the critical temperature is directly proportional to the number of preferentially attached links added to grow the network. The proposed model describes the magnetization of the majority of the sites with average or smaller than average degree better compared to the heterogeneous mean-field approximation. The long-range Ising model is the only homogeneous description of Barabási-Albert networks that we know of.

cond-mat.dis-nn↗