We consider phase transitions out of a general topological phase in $2+1$ dimensions. We assume that the transition is triggered by a single Abelian anyon, which becomes light near the transition and whose worldlines proliferate after the transition. (This proliferation is often referred to as “condensation.”) We describe the transition using a continuum field theory obtained by coupling the corresponding topological quantum field theory (TQFT) to a single complex scalar field associated with this anyon. With these assumptions, we find the most general relativistic field theory for such a transition. Even though for a given TQFT and a choice of anyon, there are infinitely many such field theories, the transition theory depends on only a single additional integer parameter. We analyze all these theories, their global symmetries, and their phases. In generic cases, the theory after the transition can be related to the original one via an Abelian hierarchy construction. In special cases, the theory after the transition is gapless, and with a particular deformation, it is related to the original TQFT by gauging an anomaly-free one-form global symmetry. We also explore the enrichment of this setup by a global $\mathrm{U}\left(1\right)$ symmetry. In some cases, enriching the original TQFT is incompatible with the full transition theory. Finally, we demonstrate our construction with many specific examples.

Using bulk gapless topological superconductors in both 1D and 2D as free fermion model examples, we demonstrate the power of subsystem correlation spectrum (the spectrum of correlation matrix), or equivalently the entanglement spectrum for the case of free fermions, in characterizing the topology of the nontrivial ground state. For the systems considered, we show that signatures of the low-energy spectrum, including both the edge modes and the bulk modes, appear in the correlation spectrum, albeit with different behaviors. This work generalizes the 2D Li-Haldane entanglement spectrum characterization of topological edge states to 2D topological systems with gapless bulk.

An anisotropic flat-band fermion system with linear dispersion along one direction and cubic dispersion along the other was proposed in Sheffer et al. [Phys. Rev. X 13, 021012 (2023)]. Here, we study the effects of long-range Coulomb interaction in this fermion system by renormalization group theory and the Dyson–Schwinger gap equation. Renormalization group analysis reveals that the fermion velocity is always restored along the direction that originally exhibits cubic dispersion. Consequently, in the low-energy regime, the system exhibits behavior similar to that of a two-dimensional Dirac fermion system subject to Coulomb interaction. Using the Dyson–Schwinger gap equation method, we find that an excitonic gap is generated if the Coulomb interaction is sufficiently strong, driving the system into a distinct excitonic insulating state with half-quantized anomalous Hall conductivity. Interestingly, we find that the excitonic gap is much more readily generated by Coulomb interaction in the anisotropic flat-band fermion system than in the Dirac fermion system. Based on this finding, we propose a strategy to observe the half-quantized anomalous Hall conductivity. We also investigate the influence of short-range four-fermion interaction on the anisotropic flat-band fermion system. It is shown that the system is driven into the excitonic insulating phase if the strength of four-fermion interaction exceeds a critical value. Observable quantities of this system in the free case, under weak Coulomb interaction, and in the gapped phase driven by strong interactions are also analyzed.

We adapt the fluid description of fractional quantum Hall states, as seen in Monteiro et al. [Phys. Rev. B 109, 174525 (2024)], to model a system of interacting two-component bosons. This system represents the simplest physical realization of an interacting bosonic symmetry-protected topological (SPT) phase, also known as the integer quantum Hall effect of bosons. In particular, we demonstrate how the fluid dynamical boundary conditions of no penetration and no stress at a hard wall naturally give rise to the two counterpropagating boundary modes expected in these SPT phases. Moreover, we identify energy-conserving hydroboundary conditions that can either create a gap in these edge modes or completely isolate the edge states from the bulk, as described in Altland et al. [Phys. Rev. X 14, 011057 (2024)], where they were termed fragile surface states. These fragile surface states are typically absent in $K$-matrix edge theories and require bulk dynamics to manifest. By leveraging insights from hydrodynamical boundary dynamics, we can further elucidate the intricate surface properties of SPTs beyond the usual topological quantum field theory-based approaches.

The ability to compute electron-phonon coupling from first principles, using density functional perturbation theory and interpolation techniques, has enabled predictive calculations of electronic transport coefficients in crystalline materials. However, these methods are still computationally expensive. Here we present two inexpensive methods to obtain thermoelectric transport properties of semiconductors using a small number of electron-phonon matrix elements calculated from first principles. The first method combines models for coupling of electrons with different phonon modes whose parameters are obtained from $\sim 10$ matrix elements per electronic band and phonon mode calculated from first principles. Within this method, we formulate the acoustic deformation potential model for arbitrary crystal symmetries and band extrema locations. The second method uses machine learning to interpolate $\sim 100$ electron-phonon matrix elements per electronic band and phonon mode on dense reciprocal-space grids in the parts of the Brillouin zone relevant for transport. We apply both methods to two-dimensional ${\mathrm{MoS}}_2$ and show very good agreement with the state-of-the-art method. The calculated thermoelectric properties also agree well with experiments. We find that the machine-learning method is more accurate and straightforward to implement compared to the model approach.

Layer twisting in graphenelike materials enables novel physical properties through an additional degree of freedom. Here, we investigate the electronic, magnetic, and thermoelectric properties of antiferromagnetic twisted bilayer graphene nanoribbons using first-principles calculations combined with the coherent transport formalism. Both armchair- and zigzag-edge configurations were examined at four representative twist angles ($\alpha =0^{\circ },13.{17}^{\circ },9.{43}^{\circ },7.{34}^{\circ }$) to explore the interplay between moiré-induced electronic reconstruction and interlayer nitrogen (N) intercalation. The results show that intercalated N atoms modify interlayer coupling and induce spin splitting in the band structure, leading to spin-dependent transport phenomena. Tuning the twist angle drives transitions among metallic, half-metallic, and spin-semiconducting states, accompanied by localized band-edge features at smaller $\alpha$. These tunable electronic and magnetic properties yield large spin-Seebeck coefficients and spin currents under thermal gradients and bias voltage. The combined effects of N-intercalated and twist modulation offer an efficient route to control spin-polarized transport and energy conversion in bilayer graphene nanostructures.

Numerical simulations with an atomistic quasiharmonic model are used to study the buckling transition of graphene membranes under compressive stress and thermal fluctuations, with free in-plane particle displacements at the boundaries. Monte Carlo methods combining collective wave moves and replica exchange at different pressures are employed, focusing on static and dynamic critical exponents through finite-size scaling. The correlation length exponent aligns well with recent renormalization-group results and is much smaller than for the strain-induced transition with clamped boundaries. At transition, the dynamic and diffusive exponents match those of freestanding graphene and strain-induced buckling transition, suggesting that stress- and strain-induced transitions share the same dynamic universality, but are in different static universality classes. The small threshold found for the buckling transition helps explain the unusual membrane velocity distributions seen experimentally in freestanding graphene.

Optical trapping enables efficient, noncontact manipulation of micro- and nanoscale particles; however, absorption-induced photothermal heating from the trapping beam can perturb trapping stability and measurement fidelity. Despite the ubiquity of optical tweezers in cutting-edge research, accurately quantifying their thermal effects remains difficult. Here, we employ an in-house integrated optical tweezers-Raman thermometry platform and use polystyrene (PS) particles as a model system to quantify local temperature rises in 2D and 3D trapping configurations. Our results indicate that interface traps exhibit a lower photothermal rise ($148.058\mathrm{K}{\mathrm{W}}^{-1}$) compared to 3D bulk traps ($217.556\mathrm{K}{\mathrm{W}}^{-1}$), due to efficient heat dissipation through the adjacent substrate. Despite the lower absolute temperature, the 2D configuration induces strong thermal gradients that drive Marangoni convection, resulting in a characteristic ringlike particle distribution. In contrast, bulk trapping results in higher thermal accumulation due to the thermal isolation of the liquid environment, yet maintains a more isotropic temperature field without interface-induced flow artifacts. These findings suggest that interface-constrained 2D trapping reduces thermal accumulation is valuable for precision measurements on thermally sensitive systems (e.g., biomolecules or temperature-dependent kinetics). Conversely, 3D trapping can be intentionally used to enhance optothermal actuation and microfluidic transport.

A high-pressure investigation of the Weyl semimetals ${\mathrm{NbIrTe}}_4$ and ${\mathrm{TaIrTe}}_4$ is presented, using infrared spectroscopy supplemented by density functional theory calculations. The experimental optical conductivity spectra as a function of pressure suggest the occurrence of a pressure-induced phase transition at a critical pressure $P_{\text{c}}=7–8\mathrm{GPa}$. This transition is most likely electronic in nature, as Raman scattering measurements provide no evidence of a significant structural phase transition. Above $P_{\text{c}}$ a significant redistribution of spectral weight occurs in the optical conductivity spectrum for both materials. A Drude-Lorentz analysis of the optical data indicates a sharp reduction in the free-carrier concentration at $P_{\text{c}}$, concomitant with the appearance of a low-energy phonon, which was initially screened by free charge carriers. A predominantly electronic origin of the phase transition is supported by the calculated electronic band structure, Fermi surface, and interband optical conductivity as a function of pressure. Our findings provide collective evidence for a pressure-induced, most likely electronic phase transition in both van der Waals materials at $P_{\text{c}}=7–8\mathrm{GPa}$, highlighting the tunability of their electronic band structure by hydrostatic pressure.

Analytic continuation aims to reconstruct real-time spectral functions from imaginary-time Green's functions; however, this process is notoriously ill-posed and challenging to solve. We propose a neural network architecture, named the Feature Learning Network (FL-net), to enhance the prediction accuracy of spectral functions, achieving an improvement of at least $20\%$ over traditional methods, such as the Maximum Entropy Method, and previous neural network approaches. Furthermore, we develop an analytical method to evaluate the robustness of the proposed network. Using this method, we demonstrate that increasing the hidden dimensionality of FL-net, while leading to lower loss, results in decreased robustness. Overall, our model provides valuable insights into effectively addressing the complex challenges associated with analytic continuation.

We investigate the ground-state phase diagram of a one-dimensional ${\mathbb{Z}}_2$ lattice gauge theory (LGT) model with hard-core bosons at half filling, extending previous studies by including second nearest-neighbor (2NN) interactions. Using matrix product state techniques within the density matrix renormalization group, we compute charge gap, static structure factor, pair-pair correlation functions, and entanglement entropy for various interaction strengths and field parameters. We analyze two representative nearest-neighbor interaction strengths ($V_1$) that correspond to the Luttinger liquid (LL) and Mott insulator (MI) phases in the absence of the 2NN interactions. We introduce the 2NN coupling $V_2$ and investigate its impact on the system. Our results reveal very rich behavior. As the 2NN repulsion increases, in the case of small $V_1$, we observe a direct transition from the LL phase to a charge-ordered insulator (COI) phase with four-site ordering pattern, whereas for large $V_1$, we observe a transition from the MI phase with two-site ordering pattern (previously found with only $V_1$ included), going through an intermediate LL region, and finally reaching the COI regime. Additionally, the inclusion of 2NN interactions enhances charge order and suppresses pair coherence, evidenced by sharp peaks in the structure factor and rapid decay in pair-pair correlators. Our work extends the well-studied phase structure of 1D ${\mathbb{Z}}_2$ LGT models and demonstrates the interplay between gauge fields, confinement, and extended interactions.

Recent experiments in moiré materials have observed fractional Chern insulators (FCIs) at zero magnetic field, providing an opportunity to study the transition from FCIs to the more conventional phases such as Fermi liquid (FL) and superconductor by tuning the interaction strength or bandwidth. In this work, we formulate a critical theory for a continuous transition at the filling $\nu =\frac{2}{3}$ between the FL and an intermediate FCI phase that hosts an additional neutral sector, but has the same transport signatures as the usual FCI. In our framework, this corresponds to a transition from a composite Fermi liquid to a ${\mathrm{superfluid}}^{*}$ phase of the composite bosons. The Fermi liquid close to the transition has an additional factor $|z_i-z_j{|}^6$ in its wave function. Also, the transport behavior at high temperature on the FL side is actually like an “anyon gas” phase on top of the FCI, with ${\rho }_{xy}$ close to $\frac{3}{2}\frac{h}{e^2}$. FL behavior with ${\rho }_{xy}\approx 0$ is recovered only at very low temperature. We also briefly discuss the possibility of a chiral superconductor as the descendant of this strongly correlated FL and the potential relevance to the twisted ${\mathrm{MoTe}}_2$ system.

${\mathrm{Cs}}_2{\mathrm{KInI}}_6$ is a promising lead-free halide double perovskite with a calculated direct band gap of $1.94\mathrm{eV}$, ideal for solar cell applications. Our first-principles calculations reveal that its cubic phase ($Fm\overline{3}m$) is dynamically unstable. Using an accelerated machine learning approach, we identify 42 dynamically stable structures and further validate these findings using first-principles calculations on 11 of these. The most stable phase has $Cmc{2}_1$ symmetry with 20 atoms/unit cell. It lies 13 meV/atom above the convex hull but lacks octahedral cation coordination. The most stable perovskitelike structure has $P\overline{3}$ symmetry with 10 atoms/unit cell and low octahedral connectivity. Structure-property trade-offs are highlighted, with calculated distortions generally widening the band gap, shifting it from direct to indirect, and flattening the band edges. This work showcases the synergy of genetic algorithms, machine-learned potentials, and first-principles validation for discovering stable, complex materials.

The graphene-diamond heterostructure has stimulated extensive research due to its potential applications in high-performance electronic devices. The fabrication of the graphene-diamond heterostructure by conventional methods often suffers from complex processing steps, weak interfacial adhesion, or low graphene coverage. Here, we present a different route for fabricating the graphene-diamond heterostructure. By utilizing manganese chemical vapor catalysis, in situ formation of carbon ${sp}^2$-on-$s{p}^3$ is successfully achieved. The as-grown graphene exhibits high coverage, relatively uniform thickness, and high electron concentration and moderate electron mobility ($1.28\times {10}^{15}\mathrm{c}{\mathrm{m}}^{-2}$ and $219\mathrm{c}{\mathrm{m}}^2{\mathrm{V}}^{-1}{\mathrm{s}}^{-1}$ at room temperature, respectively). Furthermore, both covalently bonded and van der Waals interfaces are evidenced by high-resolution transmission electron microscopy, and the charge transfer at the interfaces is revealed through density functional theory calculations. This manganese chemical vapor catalysis strategy with a simple one-step process provides a different pathway for all-carbon ${sp}^2$-on-$s{p}^3$ electronic devices, which may promote industrial-scale applications.

High-density nitrogen-vacancy (NV) ensembles, containing a large number of quantum sensors, offer great potential for enhancing the performance of quantum magnetometry. However, the high concentration of nitrogen defects in diamond introduces abundant charge donors and leads to substantial charge-state fluctuations, which impose a fundamental limitation on practical performance. In this study, we observe recharging-induced spin depolarization and spontaneous repolarization in an electron-rich NV ensemble by systematically varying the dark interval between laser and microwave pulses. Different initialization conditions influence the observed dynamics. By concurrently tracking both charge and spin dynamics, we identify long-range defect-mediated electron transport as the dominant mechanism underlying charge conversion and the associated spin-state degradation. Our findings provide insights into electron-transport dynamics in deep-level defects in diamond, and offer practical guidelines for stabilizing the ${\mathrm{NV}}^{-}$ charge state and manipulating spin polarization.

Quantum batteries provide a useful setting for exploring nonequilibrium many-body effects in energy storage. Here we investigate the optimization of a quantum battery based on the central-spin model. We identify two complementary structural indicators associated with the effective charging dynamics: one yields an upper bound on the average charging power, while the other characterizes the buildup of stored energy. We show that these two indicators are jointly optimized at a distinguished initial charger excitation number, which selects a particular Dicke sector of the model. At this common optimal point, the effective charging Hamiltonian becomes exactly mirror symmetric, suggesting mirror symmetry as a useful structural indicator for optimizing the performance of quantum batteries in terms of both charging power and energy storage. We further show that the corresponding optimal dynamics can be closely approximated by product initial states, in particular by spin coherent states whose excitation-number distribution is centered at the symmetry-selected point. Our results establish a direct connection between charging performance, optimal-state structure, and emergent symmetry in the central-spin quantum battery, and suggest symmetry as a useful organizing principle for efficient charging in interacting many-body quantum systems.

Non-Markovian memory effects have recently emerged as key factors in modeling realistic quantum thermal devices. In this work, we investigate the transient and steady-state performance of a qutrit-based quantum thermal diode model, extending the analysis beyond the commonly used weak system-environment coupling approximation, with a particular focus on how non-Markovianity influences its behavior. We employ a pseudomode-inspired auxiliary-qubit embedding combined with a Lindblad-type master equation to analyze the system, which offers an efficient framework for capturing memory effects. Numerical simulations show that moderate to strong system-bath interactions significantly modify the transient dynamics, where a selected-state BLP witness identifies information backflow. In these regimes, the state populations, coherences, and thermal flows exhibit more pronounced transient oscillations. Our results further reveal that both the steady-state thermal flows and the rectification factor are only weakly influenced by the system-environment coupling strength, indicating that non-Markovian memory effects do not play a dominant role in determining the steady-state performance in the present model. These findings highlight the importance of non-Markovian dynamics in controlling transient thermal transport, particularly in regimes where dynamical response and short-time behavior are critical, while demonstrating that steady-state rectification remains largely insensitive to memory effects in the present model.

Recently, the intriguing interplay between topology and quantum criticality has been unveiled in one-dimensional topological chains with extended nearest-neighbor couplings. In these systems, topologically distinct critical phases emerge with localized edge modes despite the vanishing bulk gap. In this work, we study the topological multicritical points at which distinct gapped and critical phases intersect. Specifically, we consider a topological chain with coupling up to the third nearest neighbors, which shows stable localized edge modes at the multicritical points. These points possess only nontrivial gapped and critical phases around them and are also characterized by the quadratic dispersion around the gap-closing points. We characterize the topological multicritical points in terms of the topological invariant obtained from the zeros of the complex function associated with the Hamiltonian. Further, we analyze the nature of zeros in the vicinity of the multicritical points by calculating the discriminants of the associated polynomial. The discriminant uniquely identifies the topological multicritical points and distinguishes them from the trivial ones. Moreover, we identify the underlying physical mechanism in terms of kinetic inversion in higher-order terms. We finally study the robustness of the zero-energy modes at the multicritical points at weak disorder strengths, and reveal the presence of a topologically nontrivial gapless Anderson-localized phase at strong disorder strengths.

Quantum batteries—miniaturized devices able to store and release energy on demand—are promising both because their intrinsic energy and timescales can match those of other quantum technologies and due to the intriguing possibility of achieving superextensive charging power. While this enhanced scaling is known to appear in several settings, it is generally believed to be forbidden in Jordan-Wigner integrable spin chains charged via quantum-quench protocols. Here, we show that an extended cluster-Ising model, despite belonging to the above category, exhibits superextensive charging power over wide ranges of system sizes, reaching up to a thousand spins, in proper parameter regimes. This remarkable anomalous scaling is due to a corresponding superextensive growth of the stored energy, implying that it is limited to a large but finite size of the system and cannot persist in the thermodynamic limit. This phenomenon appears robust against finite-temperature effects.