Intertwined charge and spin correlations are ubiquitous in a wide range of transition metal oxides and are often perceived as intimately related to unconventional superconductivity. Theoretically envisioned as driven by strong electronic correlations, the intertwined order is usually found to be strongly coupled to the lattice as signaled by pronounced phonon softening. Recently, both charge and spin density waves (CDW and SDW) and superconductivity have been discovered in several Ruddlesden-Popper (RP) nickelates, in particular trilayer nickelates $R{E}_4{\mathrm{Ni}}_3{\mathrm{O}}_{10}$ ($RE=\mathrm{Pr}$, La). The nature of the intertwined order and the role of lattice-charge coupling are at the heart of the debate about these materials. Using inelastic x-ray scattering, we mapped the low-energy phonon dispersions in $R{E}_4{\mathrm{Ni}}_3{\mathrm{O}}_{10}$ and found no evidence of softening near the CDW wave vector over a wide temperature range, which contrasts with the pronounced anomalies frequently observed in cuprate superconductors. Calculations of the electronic susceptibility revealed a peak at the observed SDW ordering vector but not at the CDW wave vector. Our experimental and theoretical findings highlight the crucial role of the spin degree of freedom and establish a foundation for understanding the interplay between superconductivity and density-wave transitions in RP nickelate superconductors and beyond.

Computing high-dimensional potential energy surfaces for molecular systems and materials is considered to be a great challenge in computational chemistry with potential impact in a range of areas including the fundamental prediction of reaction rates. In this paper, we design and discuss an algorithm that has similarities to large language models in generative AI and natural language processing. Specifically, we represent a molecular system as a graph which contains a set of nodes, edges, faces, etc. Interactions between these sets, which represent molecular subsystems in our case, are used to construct the potential energy surface for a reasonably sized chemical system with 51 nuclear dimensions. For this purpose, a family of neural networks that pertain to the graph-theoretically obtained subsystems get the job done for this 51 nuclear dimensional system. We then ask if this same family of lower-dimensional graph-based neural networks can be transformed to provide accurate predictions for a 186-dimensional potential energy surface. We find that our algorithm does provide accurate results for this larger-dimensional problem with sub-kcal/mol accuracy for the higher-dimensional potential energy surface problem. Indeed, as a result of these developments, here we produce efforts toward a full-dimensional potential energy surface for the protonated 21-water cluster (186 nuclear dimensions) at coupled-cluster single and double level accuracy.

Microwave drives are essential for implementing control and readout operations in superconducting quantum circuits. However, increasing the drive strength eventually leads to unwanted state transitions which limit the speed and fidelity of such operations. In this work, we systematically investigate such transitions in a fixed-frequency qubit subjected to microwave drives spanning a 9-GHz frequency range. We identify the physical origins of these transitions and classify them into three categories: (1) resonant energy exchange with parasitic two-level systems (TLSs), activated by drive-induced ac-Stark shifts, (2) multiphoton transitions to noncomputational states, intrinsic to the circuit Hamiltonian, and (3) inelastic scattering processes in which the drive causes a state transition in the superconducting circuit, while transferring excess energy to a spurious electromagnetic mode or TLS material defect. We show that the Floquet steady-state simulation, complemented by an electromagnetic simulation of the physical device, accurately predicts the observed transitions that do not involve TLS. Our results provide a comprehensive classification of these transitions and offer mitigation strategies through informed choices of drive frequency as well as improved circuit design.

The statistics of particles and extended excitations, such as loops and membranes, are fundamental to modern condensed matter physics, high-energy physics, and quantum information science, yet a comprehensive lattice-level framework for computing them remains elusive. In this work, we develop a universal microscopic method to determine the generalized statistics of Abelian excitations on lattices of arbitrary dimension and demonstrate it by deriving the statistics of particles, loops, and membranes in up to three spatial dimensions. Our approach constructs a sequence of local unitary operators whose many-body Berry phase encodes the desired statistical invariant. The required sequence is generated automatically from the Smith normal form of locality constraints and therefore needs no extra physical input. We prove that the resulting invariants are quantized, provide an algorithm that computes them efficiently, and show how they unify familiar braiding and fusion data of particles while also uncovering new self- and mutual statistics of loop and membrane excitations. We further demonstrate that each statistical invariant corresponds to an ’t Hooft anomaly of a generalized symmetry; we show that a nontrivial invariant both (i) obstructs gauging that symmetry and (ii) forbids any short-range-entangled (symmetry-preserving) ground state. This establishes a precise connection between microscopic lattice anomalies and many-body dynamics, providing a generalization of the Lieb-Schultz-Mattis theorem that constrains a wide class of quantum lattice systems.

Coulomb interactions among charge carriers that occupy an electronic flat band (FB) can give rise to captivating phenomena such as quantum criticality, Mott-Hubbard states, and unconventional superconductivity at different FB filling fractions. Consequently, the search for new FB materials with tunable charge carrier filling and strong interactions is a central research theme to broaden our fundamental understanding of strongly interacting quantum systems and to realize materials with novel functionalities. In this work, we present experimental evidence obtained from temperature-dependent scanning tunneling microscopy measurements for various strongly correlated states that appear in partially occupied kagome FBs of ${\mathrm{Co}}_{1-x}{\mathrm{Fe}}_x\mathrm{Sn}$ whose filling can be controlled by the Fe-doping level $x$. At elevated temperatures ($T\ge 16\mathrm{K}$), we find evidence for rotation symmetry breaking across a broad doping range $0.05<x<0.25$. Comparison with model calculations reveals that strong Coulomb interactions ($U>100\mathrm{meV}$) blend the states of two $3d$-orbital-derived FBs and impart a nematic order parameter. Introducing phase-sensitive lock-in measurements as a local scanning tunneling microscopy probe of incompressible states, we also find direct evidence for Hubbard bands in the partially filled kagome flat bands of samples with ideal Fe doping ($x=0.17$). Results from Hubbard model calculations suggest the presence of an orbital-selective Mott state in a half-filled kagome flat band. Doping-dependent measurements show that the orbital-selective Mott state descends into a correlated metal phase upon electron and hole doping, marked by a sudden collapse of the spectral gap. Our observations demonstrate that the electronic ground state of the kagome FBs sensitively depends on the complex interplay between geometric frustration, strong Coulomb repulsion, orbital degeneracy, and filling fraction at different temperatures. More broadly, our research establishes kagome lattice materials as a unique platform for novel quantum states that arise from strong electronic correlations in a topologically nontrivial FB.

We present a self-consistent many-body framework for computing phonon-limited electronic transport from first principles, incorporating both beyond-quasiparticle effects and vertex corrections. Using the recently developed first-principles $\mathrm{sc}G{D}_0$ method, we calculate spectral functions with nonperturbative effects such as broadening, satellites, and energy-dependent renormalization. We show that the $\mathrm{sc}G{D}_0$ spectral functions outperform one-shot $G_0{D}_0$ and cumulant approximations in model Hamiltonians and real materials, eliminating unphysical spectral kinks and correctly predicting the phonon emission continuum. Building on this, we introduce the self-consistent ladder formalism for transport, which captures vertex corrections due to electron-phonon interactions. This approach unifies and improves upon the two state-of-the-art approaches for first-principles phonon-limited transport: the bubble approximation and the Boltzmann transport equation. Moreover, as a charge-conserving approximation, it enables consistent calculations of the optical conductivity and dielectric function. We validate the developed method against numerically exact results for model Hamiltonians in the dilute polaronic limit and apply it to real materials. Our results show quantitative agreement with the experimental dc conductivities in intrinsic semiconductors Si and ZnO and the ${\mathrm{SrVO}}_3$ metal, as well as excellent agreement with the experimental THz optical and dielectric properties of Si and ZnO. This work unifies first-principles and many-body approaches for studying transport, opening new directions for applying many-body theory to materials with strong electron-phonon interactions.

Living cells exhibit nonequilibrium dynamics emergent from the intricate interplay between molecular motor activity and the viscoelastic cytoskeletal matrix. The deviation from thermal equilibrium can be quantified through frequency-dependent effective temperature or time-reversal symmetry breaking quantified, e.g., through the Kullback-Leibler divergence. Here, we investigate the fluctuations of an AFM tip embedded within the active cortex of mitotic human cells with and without perturbations that reduce cortex activity through inhibition of material turnover or motor proteins. While inhibition of motor activity significantly reduces both effective temperature and time irreversibility, inhibited material turnover leaves the effective temperature largely unchanged but lowers the time irreversibility and entropy production rate associated with the fluctuation-dissipation theorem violation of tip dynamics. Our experimental findings in combination with a minimal model highlight that time irreversibility, effective temperature, and entropy production rate can follow opposite trends in active living systems, challenging, in particular, the validity of effective temperature as a proxy for the distance from thermal equilibrium, particularly in the presence of mechanical changes. Furthermore, we propose that biological activity regulates the occurrence of time-asymmetric deflection spikes in the dynamics of observables, providing a previously unrecognized link between entropy production and time irreversibility.

We report measurements of phase-matched nonlinear x-ray and optical mixing from single-crystal silicon using subresonant 0.95 eV laser pulses and 9.5 keV hard x-ray pulses from the Linear Coherent Light Source free-electron laser. The mixing signal appears as energy and momentum sidebands to the elastic Bragg peak. It is proportional to the magnitude squared of the relevant temporal and spatial Fourier components of the optically induced microscopic charges and currents. We measure the first- and second-order sideband to the 220 Bragg peak and find that the efficiency is maximized when the applied field is along the reciprocal lattice vector. For an optical intensity of approximately ${10}^{12}\mathrm{W}/{\mathrm{cm}}^2$, we measure peak efficiencies of $3\times {10}^{-7}$ and $3\times {10}^{-10}$ for the first- and second-order sideband, respectively (relative to the elastic Bragg peak). The first-order sideband is consistent with induced microscopic currents along the applied electric field and an isotropic response. The second-order sideband depends nontrivially on the optical field orientation and is consistent with an anisotropic response originating from induced charges along the bonds with ${\mathrm{C}}_{3v}$ site symmetry. The results agree well with first-principles Floquet-Bloch calculations.

Twisted transition metal dichalcogenides are a new platform for realizing strongly correlated physics with high tunability. Recent transport experiments [A. Ghiotto et al., Nature (London) 597, 345 (2021)] have reported the bandwidth-driven evolution of a Mott insulator to a strange metal behavior via the tuning of a displacement field in twisted $\mathrm{WS}{\mathrm{e}}_2$ ($\mathrm{tWS}{\mathrm{e}}_2$) fixed at half filling. However, the nature of the correlated states and the related Mott physics involved in the whole process remain to be determined. Here, we unveil theoretically the evolution of the ground state of the half-filled moiré Hubbard model as applied to $\mathrm{tWS}{\mathrm{e}}_2$, transiting from a pseudogap state with Fermi arcs to a 120° Néel ordered Mott insulator, then to another pseudogap state with Fermi pockets, and eventually to a Fermi liquid via a Lifshitz transition. The pseudogap phases are definitely identified by the vanishing of quasiparticle weights over parts of the Fermi surface, with the remaining parts forming disconnected Fermi arcs or pockets with well-defined quasiparticles. We demonstrate that the Fermi arc or pocket results from the electronic band structure reconstruction driven by electron correlations, marked by the coexistence of the poles and zeros of the single-particle Green’s function. We ascribe the ground state of the strange metal featured by the linear-$T$ resistivity observed experimentally in ${\mathrm{tWSe}}_2$ to the second pseudogap state by further calculating the temperature dependence of resistivity. This work reveals the fundamental aspects of the Mottness in moiré system and will stimulate the direct probes of the underlying physics beyond transports via the angle-resolved photoemission spectroscopy and scanning tunneling microscopy.

Inspired by natural cooling processes, dissipation has become a promising approach for preparing low-energy states of quantum systems. However, the potential of dissipative protocols remains unclear beyond certain commuting Hamiltonians. This work provides significant analytical and numerical insights into the power of dissipation for preparing the ground state of noncommuting Hamiltonians. For quasi-free dissipative dynamics, including certain 1D spin systems with boundary dissipation, our results reveal a new connection between the mixing time in trace distance and the spectral properties of a non-Hermitian Hamiltonian, leading to an explicit and sharp bound on the mixing time that scales polynomially with system size. For more general spin systems, we develop a tensor network-based algorithm for constructing the Lindblad jump operator and for simulating the dynamics. Using this algorithm, we demonstrate numerically that dissipative ground state preparation protocols can achieve rapid mixing for certain 1D local Hamiltonians under bulk dissipation, with a mixing time that scales logarithmically with the system size. We then prove the rapid mixing result for certain weakly interacting spin and fermionic systems in arbitrary dimensions, extending recent results for high-temperature quantum Gibbs samplers to the zero-temperature regime. Together, these results show that dissipation can be a powerful tool for ground state preparation, with potential applications across condensed matter physics, quantum materials science, and beyond.

Biological and robotic systems often operate in confined environments where materials must be gathered without centralized control. Inspired by the effective collection strategies of aquatic worms (Lumbriculus variegatus and Tubifex tubifex), we investigate how active filaments autonomously aggregate dispersed non-Brownian passive particles. We study this process across four platforms: living worms, a robotic chain, Brownian dynamics simulations of active polymers, and a coarse-grained toy model. We show that aggregation emerges from repeated contact and body deformation—effectively, a sweeping or brooming motion—and demonstrate that clustering dynamics are governed by filament length and bending stiffness. Across systems, particle gathering follows a shared aggregation-fragmentation process, where the steady-state cluster size approximately follows a quadratic increase with the effective width of the path cleared by the filament $W$ relative to the domain size $D$. This scaling provides a minimal geometric baseline for comparison across active filamentous systems. We find that filament flexibility modulates $W$, enabling more flexible filaments to sweep larger areas and collect more particles. These results establish a unifying framework for understanding how shape and flexibility influence transport and organization in active filament systems and filamentous robots.

Qubit loss errors constitute a dominant source of noise in many quantum hardware systems, particularly in neutral-atom quantum computers. We develop a theoretical framework to effectively detect and correct loss errors in logical algorithms and leverage such loss information in decoding. Considering general quantum error correction codes and logical circuits, we introduce a delayed-erasure decoder for experimentally motivated error models which leverages information from delayed loss detection to accurately correct loss errors, even when the precise moment of the error is unknown. Using this decoder, we identify strategies for detecting and correcting loss errors based on the logical circuit structure. For deep circuits prior to logical measurement, we explore methods to integrate loss detection into syndrome extraction with minimal overhead, identifying optimal strategies depending on the qubit loss fraction in the noise and hardware capabilities. In contrast, we find that many key algorithmic subroutines involve frequent gate teleportation, shortening the circuit depth before logical measurement and naturally replacing qubits with no additional experimental overhead. We simulate this setting using a toy model algorithm for small-angle synthesis and find a significant performance improvement as the loss fraction increases. These results provide a path forward for advancing large-scale fault-tolerant quantum computation in systems with loss error detection.

Nanoscale defects such as nitrogen-vacancy (NV) centers can serve as sensitive and noninvasive probes of electromagnetic fields and fluctuations from materials, which in turn can be used to characterize these systems. Here we specifically discuss how NV centers can probe time-reversal symmetry breaking (TRSB) phenomena in low-dimensional electronic systems. We argue that the difference in relaxation rates ${\mathrm{\Gamma }}_{\pm \widehat{z}}$ of NV centers starting from $m=\pm 1$ spin states to the ground state with $m=0$ directly probes TRSB. The effect arises from the difference in the fluctuation spectrum of left- and right-polarized electromagnetic fields emanating from such materials. In the quantum Hall setting, the NV center experiences (nearly zero) large additional contribution to its relaxation due to the presence of the material when its magnetic dipole (anti)aligns with the external field. More generally, the difference in the relaxation rates is sensitive to the imaginary part of the wave-vector-dependent Hall conductivity. We argue that this can be used to determine the Hall viscosity, which can potentially distinguish candidate fractional quantum Hall states and be used to infer the pairing angular momentum in TRSB superconductors. We compute the average relaxation rate $[{\mathrm{\Gamma }}_{+\widehat{z}}+{\mathrm{\Gamma }}_{-\widehat{z}}]$ near thin film superconductors and find that it exhibits a Hebel-Slichter-like enhancement below $T_c$. The difference ${\mathrm{\Gamma }}_{+\widehat{z}}-{\mathrm{\Gamma }}_{-\widehat{z}}$ also inherits this peak but is only nonzero for $T<T_c$ and only if the superconductivity is chiral. We provide concrete estimates for observing this effect in stacked twisted bismuth strontium calcium copper oxide flakes.

${\mathrm{CeRh}}_2{\mathrm{As}}_2$ is rare among superconductors, in that the magnetic field tunes it between two distinct superconducting phases. Combined with a lack of local inversion symmetry and an upper critical field exceeding the Pauli paramagnetic limit, this excitingly suggests triplet multicomponent superconductivity. Preceding the superconducting onset, $f$-electron correlations cause long-range order, attributed both to local antiferromagnetism and itinerant (quadrupole) density waves. A magnetic field provides a significant perturbation of the $f$ electrons and may reveal the nature of the many-body correlations. Therefore, we report comprehensive magnetization and magnetotransport studies on microstructured devices in fields of up to 73 T. Applied along the $c$ axis, the field causes a low-temperature change of majority (hole) carrier density at ${\mu }_{0}H\approx 24\mathrm{T}$. By contrast, in-plane fields produce a cascade of phase transitions; the field-induced in-plane conductivity anisotropy and lack of accompanying magnetic features, plus the closed-dome nature of the overall phase boundary is consistent with a hierarchy of field-induced density-wave states.

Secure multiparty computation enables the joint evaluation of multivariate functions across distributed users while ensuring the privacy of their local inputs. This field has become urgent due to the demand for computationally intensive deep learning inference. These computations are typically offloaded to cloud servers, leading to vulnerabilities. To solve this problem, we introduce a linear algebra engine that leverages the quantum nature of light for information-theoretically secure multiparty inference using telecommunication components. We apply this linear algebra engine to deep learning and derive rigorous upper bounds on the information leakage of both the deep neural network weights and the client’s data, enabling double-blind operations. Applied to the modified National Institute of Standards and Technology classification task, we obtain test accuracies exceeding 95% while guaranteeing leakage of less than 0.1 bits per weight and data element. This leakage is an order of magnitude below the minimum bit precision required for accurate deep learning using state-of-the-art quantization techniques. Our work lays the foundation for practical quantum-secure computation and unlocks secure cloud deep learning as a field.

The recent observation of superconductivity in the vicinity of Fermi surface reconstructed insulating or metallic states has established twisted bilayers of ${\mathrm{WSe}}_2$ as an exciting platform to study the interplay of strong electron-electron interactions, broken symmetries, and topology. In this work, we use a first-principles, material-specific theoretical treatment that is unbiased with respect to electronic instabilities to study the emergence of electronic ordering in twisted ${\mathrm{WSe}}_2$ driven by gate-screened Coulomb interactions. We construct exponentially localized moiré Wannier orbitals that faithfully capture the band structure and topology of the system, project the gate-screened Coulomb interaction onto them, and use unbiased functional renormalization group techniques to resolve the momentum and orbital structure of the leading instabilities and the relevant energy scales. We find an interplay between intervalley-coherent antiferromagnetic (IVC-AFM) order and chiral, mixed-parity $d/p$-wave superconductivity for carrier concentrations near a displacement field and twist-angle-tunable van Hove singularity. Our microscopic approach establishes incommensurate IVC-AFM spin fluctuations as the dominant electronic mechanism driving the formation of superconductivity in $\theta =5.08°$ twisted ${\mathrm{WSe}}_2$ and explains key aspects of recent experiments including the asymmetric density dependence of the spin ordering with respect to the van Hove line, the single- and double-peak structure of the DOS in the ordered (hole-doped) IVC-AFM phase, the emergence of superconductivity as the density is varied across the van Hove line, and the evolution of the displacement field-density phase diagram with twist angles between $3.7°\dots 5°$. We show that the interplay of electronic correlations and nontrivial quantum geometry in ${\mathrm{tWSe}}_2$ manifests in orbital-selective order parameters associated to the IVC-AFM and SC states that are detectable by local spectroscopy measurements.

Two-dimensional hybrid metal-halide perovskites (2D-MHPs) have emerged as important solution-processed semiconductors with favorable optical and electronic properties for diverse applications in photovoltaics, optoelectronics, and spintronics. The quasi-2D layered structures, featuring large acoustic impedance mismatches between the organic and inorganic sublattices, are expected to result in distinct and anisotropic thermal transport properties along the cross-plane and in-plane directions. Here, we introduce transducer-free vibrational-pump-visible-probe (VPVP) approaches that enable accurate quantification of anisotropic thermal transport properties in various archetypical single-crystalline 2D-MHPs. Specifically, using VPVP spectroscopy and VPVP microscopy, we measure the anisotropic thermal diffusivities of 2D-MHPs with systematically varied Pb-I octahedral layer thicknesses, as well as organic spacer types and lengths, revealing how these structural parameters alter the cross-plane and in-plane thermal transport properties in distinct ways. While diffuse interface scattering plays an important role in dictating cross-plane thermal transport, in-plane thermal transport is primarily determined by phonon transport within interconnected inorganic layers. Density functional theory incorporating four-phonon scatterings provides further insight into the low thermal conductivity and modest thermal conduction anisotropy in 2D-MHPs. Our work demonstrates a new all-optical and noncontact method, which requires minimal sample preparation and allows direct visualization of cross-plane and in-plane thermal transport, potentially compatible with in situ sample environments. The demonstrated VPVP approaches can advance understanding of thermal transport in 2D-MHPs as well as wide-ranging hybrid and polymeric semiconductors beyond 2D-MHPs.

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware-software-wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

We show that Clifford algebras provide a natural language to describe the physics of liquid crystal defects in 3D. This framework shows that most of these defects have fermionic nature, as the director field profile on a 2D cross section can algebraically be represented by a spinor. Defects in uniaxial, biaxial nematics, and cholesterics are represented by elements belonging to different Clifford algebras, suggesting that there are fundamental distinctions between topological defects in each of these phases. Our theory allows nematic defects to be interpreted as Majorana-like spinors, as defects and antidefects are topologically equivalent, while some cholesteric defects, such as screw dislocations, are better viewed as Weyl-like spinors of well-defined chirality. Defects can be described by a “defect bivector,” an algebraic element that quantifies the rototranslation associated with them. In cholesterics, fermionic defects of different types can combine to yield composite quasiparticles with either fermionic or bosonic nature. Under cylindrical confinement, these quasiparticles provide the way to understand the structure of screw dislocations. In the bulk, they may condensate to form topological phases, such as blue phases or skyrmion lattices. Our results provide a surprising link between liquid crystals, particle physics, and topological quantum matter.