Horizontally extended plane-layer convection flows are characterized by characteristic patterns of turbulent heat transfer due to the convective fluid motion consisting of a nearly regular ridge network where hot fluid rises and cold fluid sinks. Here, we analyze this transport behavior by the so-called inflated generator framework, which identifies quasistationary families of almost-invariant sets, derived from leading inflated generator eigenvectors. We demonstrate the effectiveness of this data-driven analysis framework in three-dimensional turbulent flow, by extracting transient characteristic heat transfer patterns as families of almost-invariant sets subject to a gradual evolution, which contribute least to the convective heat transfer.

We analyze the conditional quantum state of a mechanical mirror in an optomechanical system subject to continuous measurement, feedback control, and quantum filtering. We identify a parameter regime in which the mirror exhibits momentum squeezing beyond the standard quantum limit, achieved through an appropriate choice of the homodyne detection angle. In this regime, we show that optimal filtering effectively realizes a free-particle-like conditional state. When this mechanism is applied to a configuration consisting of two optomechanical systems, the resulting momentum squeezing significantly enhances the signal of gravity-induced entanglement. This enhancement arises because the momentum squeezing not only amplifies the distinction between the common and differential modes, but also, in the high-purity regime, increases the position uncertainty in accordance with the uncertainty principle, thereby enlarging the spatial extent of the quantum superposition. Our results provide insights into experimental strategies for probing the quantum nature of gravity using optomechanical platforms.

The environment surrounding a tumor plays a crucial role in cancer cell dissemination. Within this microenvironment, cancer-associated fibroblasts (CAFs) can collectively combine their tensile stress to actively remodel tumors. Using in vitro circular clusters of cancer cell monolayers surrounded by CAFs, we generate structures that are reminiscent of multicellular buds observed in vivo for colorectal cancer. A supracellular contractile ring spontaneously assembles at the inner edge of the CAF monolayer and drives its closure on top of the cancer cells through a purse-string mechanism. This CAF-driven constriction triggers multilayering of cancer cells, culminating in the growth of a bud pinched by the CAF ring. We propose that this process is powered by frictional shear stress from CAF motion and develop a theoretical model based on continuum mechanics that quantitatively reproduces the experimental observations. The model captures the early reshaping of the cancer cell layer. Invoking a generic deformation threshold for multilayering, it identifies the physical conditions that favor budding and predicts how budding probability and size scale with initial cluster diameter. Our results establish a general framework for friction-induced morphogenesis in cell layers and reveal how active mechanical coupling between tumors and their microenvironment can shape tumor morphology and behavior.

Quantum friction is a friction force caused by electromagnetic fluctuations as an atom moves relative to macroscopic bodies. This effect is only predicted theoretically and requires high velocity and close proximity to give a significant signal. To date, experiments have not been able to measure this effect. Recent experiments with ultrafast atoms have sent neutral atoms through the crystal structure of monolayer graphene [Science 389, 724 (2025)]. We present a theoretical framework describing quantum friction as atoms pass through monolayers and calculate the force on helium passing through graphene. Once the atom passes the monolayer, we find that the velocity-dependent force no longer opposes the direction of motion due to strong interactions caused by having been closer to the monolayer in the past. For the experimental parameters, we find a kinetic energy loss caused by quantum friction on the order of ten to hundred $\mu \mathrm{eV}$. We find that quantum friction cannot be measured with this setup with current techniques.

Identifying physical mechanisms that preserve the integrity of structured waves under propagation through complex environments is one of the central problems in wave physics. Here, we show that the purity of orbital angular momentum (OAM) modes can be protected against degradation in random media by leveraging two fundamental features of their own Schrödinger Hamiltonian dynamics, namely, Zeno effect—frequent observations slow down the evolution—and Gouy phase—the backaction of the observation. Repeated, OAM-dependent Gouy phase kicks imparted along the disturbing path by simple imaging systems trigger the optical Zeno effect that protects the input OAM mode against mode crosstalk that would broaden the OAM spectrum. Given the universality of the mechanism, the Gouy phase-assisted Zeno effect would protect propagation modes other than those of OAM, and the diverse forms of structured light built with them.

Conditional-$\pi$ phase shift between two photons is essential for entanglement generation and universal quantum logic. For photons, however, direct conditional controls are not possible and must be mediated by nonlinear media. Achieving such operations for photonic polarization qubits has remained difficult due to intrinsically weak photon-photon nonlinearities in atomic systems. Here, we show that a conditional-$\pi$ phase shift between two weak coherent pulses can be realized via a cavityless closed double-$\mathrm{\Lambda }$ atomic system, where quantum interference between linear and nonlinear atom-photon interactions enables conditional control. By optimizing the interaction parameters, including amplitude and phase compensations, we identify the conditions for conditional-$\pi$ phase shift between two weak coherent pulses. Experimentally, we observe the conditional-$\pi$ phase shift with relative output amplitude $0.74\pm 0.06$ and phase shift $(0.95\pm 0.03)\pi$ between the two-photon amplitudes $|HH\rangle$ and $|VV\rangle$. A theoretical analysis of Bell-state generation from weak coherent pulses further shows Clauser-Horne-Shimony-Holt inequality violation and nonzero concurrence. Our results clarify both the theoretical requirements and the experimental feasibility of cavityless atom-mediated nonlinearities for photonic quantum logic, establishing a scalable route toward nonlinear quantum photonics.

The topology of ${\mathrm{WTe}}_2$, a transition-metal dichalcogenide with large spin-orbit interactions, is thought to combine type II Weyl semimetal and second-order topological insulator (SOTI) character. The SOTI character should endow ${\mathrm{WTe}}_2$ multilayer crystals with topologically protected helical states at their hinges, and, indeed, one-dimensional states have been detected thanks to Josephson interferometry. However, the immunity to backscattering conferred to those states by their helical nature has so far not been tested. To probe the topological protection of ${\mathrm{WTe}}_2$ edge states, we have fabricated superconducting quantum interference devices (SQUIDs) in which the supercurrent through a junction on the crystal edge interferes with the supercurrent through a junction in the bulk of the crystal. We find behaviors ranging from a symmetric SQUID to asymmetric SQUID patterns, including one in which the modulation by magnetic field reveals a sawtoothlike supercurrent versus phase relation for the edge junction, demonstrating that the supercurrent at the edge is carried by ballistic channels over 600 nm, a telltale sign of the SOTI character of multilayer ${\mathrm{WTe}}_2$.

Circadian rhythms in living organisms are temporal orders emerging from biochemical circuits driven out of equilibrium. Here, considering the KaiABC system, a minimal model in the synthetic biology, we study how the oscillation emerges from the circuit made of three Kai proteins and ATP alone. The phase diagram constructed in terms of KaiC and KaiA concentrations reveals a narrowly bounded oscillatory phase, which naturally explains arrhythmia upon protein overexpression. As dictated by the cost-precision trade-offs of the thermodynamic uncertainty relations, the presence of intrinsic noise, amplified in small systems, demands higher free energy cost to achieve greater rhythmic precision. The cost-minimizing condition within the oscillatory phase is found to generate $\sim 21$-h rhythm, which is entrained to 24-h environmental signals as long as the forcing amplitude is greater than $\sim 10$% of the metabolic rate. An optimal level of intrinsic noise can also induce oscillations even beyond the Hopf bifurcation, effectively expanding the oscillatory phase. Our study clarifies how the physical factors, such as regulatory mechanism, energy cost, and stochastic noise, contribute to the operation of biological clocks.

We report on the shift of energies released during Auger cascades in rare-gas ions, when the ions are not isolated but embedded in a homogeneous cluster. By combining high-resolution electron spectroscopy with multielectron coincidence spectroscopy of small Ar and Xe clusters, we investigate the dependence of Auger electron emission energies on the charge state of the emitting ion in the polarizable cluster medium up to charge states of $+4$. Our results show deviations from the predictions of the established electrostatic Born model by a factor of $\approx 2$ for the final step of the cascades.

Erasure of the binary memory, 0 or 1, is an essential step for digital computation as it involves irreversible logic operations. In the classical case, the erasure of a bit of memory is accompanied by the evolution of a minimum amount of heat set by the Landauer bound $k_{B}Tln2$, which can be achieved in the asymptotic limit. However, the erasure of memory needs to be completed within a finite time for practical and effective computational processes. It is observed that the higher the speed of erasure, the greater the amount of heat released, which leads to unfavorable environmental conditions. Therefore, this is a fundamental challenge to reduce the evolved heat related to finite-time memory erasure. In the present work, we address this crucial aspect in the field of information thermodynamics. We proceed by considering the physical model framework where the two memory states correspond to the two wells of a bistable potential, as in the conventional cases. However, the potential is asymmetric in terms of the width of the two wells. Moreover, the two memory states are separated by a barrier that is asymmetric in structure. This type of asymmetry models the two binary memory states that occupy different phase-space volumes, although they are energetically equivalent, in a general setup. We examine in detail the effect of the degree of asymmetry on the success rate of the erasure process and the work done or heat released associated with it. We find that the asymmetry in the width of the potential wells and the barrier partitioning them, i.e., the two memory states, plays a very significant role in improving the efficiency of the erasure process, in view of the success rate and the thermodynamic costs. Our thorough simulation study establishes the fact that one can reach below the Landauer bound in an appropriate asymmetric setup. Importantly, it develops a quantitative understanding of the deviation from the Landauer limit as a function of the degree of asymmetry of the potential governing the erasure mechanism. Moreover, through our current work, we identify the effective free energy change for the finite-time bit erasure process as a general lower bound for the work done or evolved heat even when the departure from the Landauer limit is observed. We retrieve the approach toward the Landauer limit in terms of the energetics involved with the erasure mechanism under the symmetric setup.

We address the problem of implementing bottleneck layers from classical pretrained neural networks on a quantum computer, with the goal of exploring intrinsically quantum ansatz for representing large linear layers within hybrid classical-quantum models. Our approach begins with a compression step in which the target linear layer is represented as an effective matrix product operator (MPO) without degrading model performance. The MPO is then further disentangled into a more compact form. This enables a hybrid classical-quantum execution scheme, where the disentangling circuits are deployed on a quantum computer while the remainder of the network—including the disentangled MPO—runs on classical hardware. We introduce two complementary algorithms for MPO disentangling: (1) an explicitly disentangling variational method leveraging standard tensor network optimization techniques and (2) an implicitly disentangling gradient-descent-based approach. We validate these methods through a proof-of-concept translation of simple classical neural networks for MNIST and CIFAR-10 image classification into a hybrid classical-quantum form.

The functional renormalization group (fRG) is acknowledged as a powerful tool in quantum many-body physics and beyond. On the technical side, conventional implementations of the fRG rely on regulators for bare propagators only. Starting from Schwinger-Dyson and Bethe-Salpeter equations, we develop here an fRG formulation where both bare propagators and bare interactions can be dressed with regulators. The approach thus obtained is an extension of the multiloop fRG recently introduced for many-fermion systems. Using the single-boson exchange decomposition, we show that the underlying flow equations are simply interpreted as adding a regulator to the bosonic propagator and that such an extension scarcely changes the original structure of the flow equations. Overall, we provide a framework for implementing approaches that cannot be realized with conventional fRG methods, such as temperature flows for models with retarded interactions. For concrete applications, we analyze the loop convergence of our formulation against a conventional cutoff scheme for the Anderson impurity model. Finally, we devise a temperature-flow scheme that implements a cutoff in both the propagator and the bare interaction, and demonstrate its validity on a model of an Anderson impurity coupled to a phonon.

Recent advances in quantum computing have demonstrated its potential to significantly enhance the analysis and forecasting of complex classical data. Among these, quantum reservoir computing (QRC) has emerged as a particularly powerful approach, combining quantum computation with machine learning for modeling nonlinear temporal dependencies in high-dimensional time series. As with many data-driven disciplines, quantitative finance and econometrics can hugely benefit from emerging quantum technologies. In this work, we investigate the application of QRC for realized volatility forecasting. Our model employs a fully connected transverse-field Ising Hamiltonian as the reservoir with distinct input and memory qubits to capture temporal dependencies. The QRC approach is benchmarked against several econometric models and standard machine learning algorithms. The models are evaluated using multiple error metrics and the model confidence set procedures. To enhance interpretability and mitigate current quantum hardware limitations, we utilize wrapper-based forward selection for feature selection, identifying optimal subsets and quantifying feature importance via Shapley values. Our results indicate that the proposed quantum reservoir approach consistently outperforms benchmark models across various metrics, highlighting its potential for financial forecasting despite existing quantum hardware constraints. This work serves as a proof of concept for the applicability of quantum computing in econometrics and financial analysis, paving the way for further research into quantum-enhanced predictive modeling as quantum hardware capabilities continue to advance.

Although many animals rely on visual information to navigate, optic flow is inherently ambiguous as it confounds information about motion speed and object distance. As a result, the visual feedback produced by a given motor command is context dependent and requires an appropriately adapted response. Recent experiments have investigated how the fish Danionella cerebrum use visual cues to stabilize their position against simulated external currents. Logarithmic sensorimotor transformations have been proposed to enable adaptive responses to perturbations while preventing delay-induced instabilities. Here, we develop the theoretical framework introduced for continuous locomotion to show how logarithmic coding naturally gives rise to this adaptive behavior. The system is modeled by a nonlinear delay differential equation, which is analyzed using dynamical systems theory. We further analyze experimental data to uncover the mechanisms underlying swimming initiation and positional drift correction. Finally, we extend our framework to intermittent locomotion, resulting in a nonlinear difference equation, and show that it still produces robust adaptive behavior. This is motivated by the literature on zebrafish, where visuomotor stabilization has been extensively studied, but burst-and-coast swimming obscures the underlying adaptation mechanism. We show that our theory can reproduce the experimental results reported for motor adaptation in zebrafish without invoking internal models. Overall, our results highlight logarithmic coding as a unifying principle for visuomotor stability across continuous and intermittent locomotor regimes.

Quantum harmonic oscillators serve as fundamental building blocks for quantum information processing, particularly in the context of the bosonic circuit quantum electrodynamics (cQED) platform. Conventional methods for extracting oscillator properties rely on predefined analytical gate sequences to access a restricted set of observables or resource-intensive tomography processes. Here, we introduce the Optimized Routine for Estimation of any Observable (OREO), a numerically optimized protocol that maps the expectation value of arbitrary oscillator observables onto that of an ancillary qubit. We demonstrate OREO in a bosonic cQED system as a means to efficiently measure phase-space quadratures and their higher moments, directly obtain faithful non-Gaussianity ranks, and effectively achieve state preparation independent of initial conditions in the oscillator. These results position OREO as a valuable tool for direct and efficient information extraction from bosonic quantum states, unlocking possibilities for measurement, control, and state preparation in continuous-variable quantum information processing.

In genuine nonequilibrium systems under continuous driving, thermodynamic forces are nonconservative and cannot be described by any free energy potential. Nonetheless, we show that such systems can be associated with a generalized free energy derived from a large-deviation variational principle. This variational principle yields a decomposition of fluxes, forces, and entropy production into a conservative excess part and a nonconservative housekeeping part, exemplifying an information-geometric Pythagorean theorem. The decomposition is broadly applicable—including to stochastic master equations as well as closed and open deterministic chemical reaction networks—and accessible to thermodynamic inference from short-time trajectory data. We also show that the excess entropy production obeys a thermodynamic speed limit bounding the rate of state evolution and external fluxes. We illustrate the framework on driven Markov jump processes, nonlinear chemical oscillators, and real-world metabolic networks, where we obtain tight dissipation bounds and identify futile metabolic cycles. Connections are drawn to large deviations, Onsager theory, and previous excess/housekeeping decompositions.