A common expectation is that career productivity peaks rather early and then gradually declines with seniority. But whether this holds true is still an open question. Here we investigate the productivity trajectories of almost 8500 scientists from over 50 disciplines using methods from time-series analysis, dimensionality reduction, and network science, showing that there exist six universal productivity patterns in research. Based on clusters of productivity trajectories and network representations where researchers with similar productivity patterns are connected, we identify constant, u-shaped, decreasing, periodic-like, increasing, and canonical productivity patterns, with the latter two describing almost three-fourths of researchers. In fact, we find that canonical curves are the most prevalent, but contrary to expectations, productivity peaks occur much more frequently around midcareer rather than early. These results outline the boundaries of possible career paths in science and caution against the adoption of stereotypes in tenure and funding decisions.

The spontaneous emergence of scale invariance, called self-organized criticality (SOC), is often attributed to a second-order absorbing-state phase transition (ASPT). Many real-world systems display SOC, yet with extreme events overrepresented, called dragon kings (DKs) and causing significant disruption. We show analytically that the trade-off between driving impulse and dissipation rate can create DKs in a second-order ASPT. This establishes that DKs exist in SOC systems, reveals a taxonomy of DKs, and shows that larger dissipation and smoother driving lower risk of extreme events.

This article is part of the Physical Review Research collection titled Physics of Neuroscience.

Recurrent networks are widely used as models of biological neural circuits and in artificial intelligence applications. Mean-field theory has been used to uncover key properties of recurrent network models such as the onset of chaos and their largest Lyapunov exponents, but quantities such as attractor dimension and Kolmogorov-Sinai entropy have thus far remained elusive. We calculate the complete Lyapunov spectrum of recurrent neural networks and show that chaos in these networks is extensive with a size-invariant Lyapunov spectrum and attractor dimensions much smaller than the number of phase space dimensions. The attractor dimension and entropy rate increase with coupling strength near the onset of chaos but decrease far from the onset, reflecting a reduction in the number of unstable directions. We analytically approximate the full Lyapunov spectrum using random matrix theory near the onset of chaos for strong coupling and discrete-time dynamics. We show that a generalized time-reversal symmetry of the network dynamics induces a point symmetry of the Lyapunov spectrum reminiscent of the symplectic structure of chaotic Hamiltonian systems. Temporally fluctuating input can drastically reduce both the entropy rate and the attractor dimension. We lay out a comprehensive set of controls for the accuracy and convergence of Lyapunov exponents. For trained recurrent networks, we find that Lyapunov spectrum analysis quantifies error propagation and stability achieved by different learning algorithms. Our methods apply to systems of arbitrary connectivity and highlight the potential of Lyapunov spectrum analysis as a diagnostic for machine learning applications of recurrent networks.

We study the magnetic Rayleigh-Taylor instability in relativistic collisionless plasma, as an astrophysical process for nonthermal particle acceleration. We consider dense plasma on top of a highly magnetized cavity with sheared magnetic field. Using particle-in-cell simulations, we show that small plumes grow and merge progressively to form a large-scale plume, which broadens to drive rapid magnetic reconnection in the cavity. We find that this leads to efficient particle acceleration capable of explaining flares from the inner accretion flow onto the black hole Sgr A*.

We demonstrate optical sideband spectroscopy of a single ${}^9\mathrm{Be}^{+}$ ion in a cryogenic 5 tesla Penning trap using two-photon stimulated-Raman transitions between the two Zeeman sublevels of the $1s^{2}2s$ ground state manifold. By applying two complementary coupling schemes, we accurately measure Raman resonances with and without contributions from motional sidebands. From the latter we obtain an axial sideband spectrum with an effective mode temperature of $(3.1\pm 0.4)$ mK. These results are a key step for quantum logic operations in Penning traps, applicable to high-precision matter-antimatter comparison tests in the baryonic sector of the standard model.

We consider the dynamics of active nematics droplets on flat surfaces, based on the continuum hydrodynamic theory. We investigate a wide range of dynamical regimes as a function of the activity and droplet size on surfaces characterized by strong anchoring and a range of equilibrium contact angles. The activity was found to control a variety of dynamical regimes, including the self-propulsion of droplets on surfaces, scission, active wetting, and droplet evaporation. Furthermore, we found that on a given surface (characterized by the anchoring and the equilibrium contact angle) the dynamical regimes may be controlled by the active capillary number of suspended droplets. We also found that the active nematics concentration of the droplets varies with the activity, affecting the wetting behavior weakly but ultimately driving droplet evaporation. Our analysis provides a global description of a wide range of dynamical regimes reported for active nematics droplets and suggests a unified description of droplets on surfaces. We discuss the key role of the finite size of the droplet and comment on the suppression of these regimes in the infinite-size limit, where the active nematics is turbulent at any degree of activity.

A common way to entangle quantum memories is via photonic entanglement swaps. Each of two memories, connected by an optical channel, emits a photonic qubit entangled with itself, and the photonic qubits undergo an entanglement swap on a beamsplitter in the middle of the channel. We compare two choices of encoding of the photonic qubit: single rail and dual rail. At low channel loss the dual-rail scheme outperforms the single-rail scheme. However, as expected, the high-loss rate asymptote for the dual-rail scheme scales quadratically worse with loss compared with single rail. Considering the following nonidealities: imperfect mode matching at the swap, carrier-phase mismatch across the interfered photonic qubits, and detector excess noise, we evaluate the density operator of the heralded two-qubit entangled state. We calculate a lower bound on its distillable entanglement per copy, and its fidelity (with the ideal Bell state). For both schemes, imperfect swap-visibility results in a constant-factor decrease in the rate, while excess noise results in a dropoff of distillable entanglement beyond a certain total channel loss threshold, to zero. Despite the single-rail scheme's better rate-loss scaling, it is more severely affected by excess noise. The single-rail scheme is adversely affected by stochastic carrier-phase mismatch, which does not affect the dual-rail scheme. We study entanglement distillation on the heralded noisy entangled states for both methods and outline a suite of quantum networking studies that our work could incite.

We report on the preparation of a pure ultracold sample of bosonic DyK Feshbach molecules, composed of the fermionic isotopes ${}^{161}\mathrm{Dy}$ and ${}^{40}\mathrm{K}$. By sweeping a magnetic field across a resonance located near 7.3 G, we generate up to 5000 molecules at a temperature of approximately 50 nK. To purify the sample from remaining atoms, we employ a Stern-Gerlach technique that relies on magnetic levitation of the molecules in a very weak optical dipole trap. With the trapped molecules we finally reach a high phase-space density of about 0.1. We investigate the magnetic field dependence of the molecular binding energy and the magnetic moment, refining our knowledge of the resonance parameters. We also demonstrate a peculiar anisotropic expansion effect observed when the molecules are released from the trap and expand freely in the magnetic levitation field. Furthermore, we identify an important lifetime limitation that is imposed by the 1064-nm infrared trap light itself and not by inelastic collisions. The light-induced decay rate is found to be proportional to the trap light intensity and the closed-channel fraction of the Feshbach molecule. These observations suggest a one-photon coupling to electronically excited states to limit the lifetime and point to the prospect of loss suppression by optimizing the wavelength of the trapping light. Our results offer crucial insights and experimental progress towards achieving quantum-degenerate samples of DyK molecules and novel superfluids based on mass-imbalanced fermion mixtures.

We show that pressure applied to twisted ${\mathrm{WSe}}_2$ can enhance the many-body gap and region of stability of a fractional Chern insulator at filling $\nu =1/3$. Our results are based on exact diagonalization of a continuum model, whose pressure dependence is obtained through ab initio methods. We interpret our results in terms of a magic line in the pressure-vs-twist angle phase diagram: along the magic line, the bandwidth of the topmost moiré valence band is minimized while simultaneously its quantum geometry resembles that of an ideal Chern band. We expect our results to generalize to other twisted transition metal dichalcogenide homobilayers.

Recent experimental advances have made it possible to detect individual quantum jumps in open quantum systems, such as the tunneling of single electrons in nanoscale conductors or the emission of photons from nonclassical light sources. Here, we investigate theoretically the statistics of photons emitted from a microwave cavity that is driven resonantly by an external field. We focus on the differences between a parametric and a coherent drive, which either squeezes or displaces the cavity field. We employ a Lindblad master equation dressed with counting fields to obtain the generating function of the photon emission statistics using a theoretical framework based on Gaussian states. We then compare the distribution of photon waiting times for the two drives as well as the $g^{\left(2\right)}$ functions of the outgoing light, and we identify important differences between these observables. In the long-time limit, we analyze the factorial cumulants of the photon emission statistics and the large-deviation statistics of the emission currents, which are markedly different for the two drives. Our theoretical framework can readily be extended to more complicated systems, for instance, with several coupled microwave cavities, and our predictions may be tested in future experiments.

Angle-resolved photoemission spectroscopy (ARPES) is a method that measures orbital and band structure contrast through the momentum distribution of photoelectrons. Its simplest interpretation is obtained in the plane-wave approximation, according to which photoelectrons propagate freely to the detector. The photoelectron momentum distribution is then essentially given by the Fourier transform of the real-space orbital. While the plane-wave approximation is remarkably successful in describing the momentum distributions of aromatic compounds, it generally fails to capture kinetic-energy-dependent final-state interference and dichroism effects. Focusing our present study on quasi-freestanding monolayer graphene as the archetypical two-dimensional (2D) material, we observe an exemplary $E_{\mathrm{kin}}$-dependent modulation of, and a redistribution of spectral weight within, its characteristic horseshoe signature around the $\overline{\text{K}}$ and ${\overline{\text{K}}}^{\prime }$ points: both effects indeed cannot be rationalized by the plane-wave final state. Our data are, however, in remarkable agreement with ab initio time-dependent density functional simulations of a freestanding graphene layer and can be explained by a simple extension of the plane-wave final state, permitting the two dipole-allowed partial waves emitted from the C $2p_z$ orbitals to scatter in the potential of their immediate surroundings. Exploiting the absolute photon flux calibration of the Metrology Light Source, this scattered-wave approximation allows us to extract $E_{\text{kin}}$-dependent amplitudes and phases of both partial waves directly from photoemission data. The scattered-wave approximation thus represents a powerful yet intuitive refinement of the plane-wave final state in photoemission of 2D materials and beyond.

In a recent Letter [T. Dornheim et al., Phys. Rev. Lett. 121, 255001 (2018)], it was predicted on the basis of ab initio quantum Monte Carlo simulations that, in a uniform electron gas, the peak ${\omega }_0$ of the dynamic structure factor $S(q,\omega )$ exhibits an unusual nonmonotonic wave number dependence, where $d{\omega }_0/dq<0$, at intermediate $q$, under strong coupling conditions. This effect was subsequently explained by the pair alignment of electrons [T. Dornheim et al., Commun. Phys. 5, 304 (2022)]. Here we predict that this nonmonotonic dispersion resembling the roton-type behavior known from superfluids should be observable in a dense, partially ionized hydrogen plasma. Based on a combination of path integral Monte Carlo simulations and linear response results for the density response function, we present the approximate range of densities, temperatures and wave numbers and make predictions for possible experimental observations.

Agent-based models of opinion dynamics allow one to examine the spread of opinions between entities and to study phenomena such as consensus, polarization, and fragmentation. By studying models of opinion dynamics on social networks, one can explore the effects of network structure on these phenomena. In social networks, some individuals share their ideas and opinions more frequently than others. These disparities can arise from heterogeneous sociabilities, heterogeneous activity levels, different prevalences to share opinions when engaging in a social-media platform, or something else. To examine the impact of such heterogeneities on opinion dynamics, we generalize the Deffuant-Weisbuch (DW) bounded-confidence model (BCM) of opinion dynamics by incorporating node weights. The node weights allow us to model agents with different probabilities of interacting. Using numerical simulations, we systematically investigate (using a variety of network structures and node-weight distributions) the effects of node weights, which we assign uniformly at random to the nodes. We demonstrate that introducing heterogeneous node weights results in longer convergence times and more opinion fragmentation than in a baseline DW model. The node weights in our BCM allow one to consider a variety of sociological scenarios in which agents have heterogeneous probabilities of interacting with other agents.

Recent works have shown that the magnetization of Tb/Co multilayers can be switched all-optically by a single ultrashort laser pulse. Surprisingly, the same process cannot be achieved in TbCo alloys. Here, we present a plausible explanation for this difference in behavior based on the known treatment of angular momenta and the associated gyromagnetic ratio of rare-earth-based ferrimagnets. We then study in detail the composition-dependent dynamic behavior of the switching process in Tb/Co multilayers using single-shot time-resolved pump-probe experiments. We show that the observed dynamics is strongly dependent on the excitation fluence and multilayer composition and does not fit into the accepted framework describing the single-shot switching process found in Gd-based systems and Mn-containing Heusler alloys.

Many-body cavity QED experiments are established platforms to tailor and control the collective responses of ensembles of atoms, interacting through one or more common photonic modes. The rich diversity of dynamical phases they can host calls for a unified framework. Here we commence this program by showing that a cavity QED simulator assembled from $N$-level bosonic atoms can reproduce and extend the possible dynamical responses of collective observables occurring after a quench. Specifically, by initializing the atoms in classical or quantum states, or by leveraging intralevels quantum correlations, we craft on demand the entire synchronization/desynchronization dynamical crossover of an exchange model for SU(N) spins. We quantitatively predict the onset of different dynamical responses by combining the Liouville-Arnold theorem on classical integrability with an ansatz for reducing the collective evolution to an effective few-body dynamics. Among them, we discover a synchronized chaotic phase induced by quantum correlations and associated to a first-order nonequilibrium transition in the Lyapunov exponent of collective atomic dynamics. Our outreach includes extensions to other spin-exchange quantum simulators and a universal conjecture for the dynamical reduction of nonintegrable all-to-all interacting systems.

We investigate the mechanical origin of polymorphic structures in two-dimensional tubulin assemblies, of which microtubules are the best known example. These structures feature twisted ribbons, flat tubulin sheets, macrotubules, and hoops, and they spontaneously assemble depending on the chemical environment. Upon modeling tubulin aggregates as minimally anisotropic elastic shells and using a combination of numerical simulations and analytical work, we show that the mechanical strain in tubulin lattices, originating from asymmetries at the single dimer level, naturally gives rise to polymorphic assemblies, among which cylinders and other tubular structures are predominant for a wide range of values of the spontaneous curvature. Furthermore, our model suggests that switching the sign of the sheets' spontaneous Gaussian curvature from positive (i.e., sphere-like) to negative (i.e., saddle-like), could provide a possible route to microtubules disassembly. Our paper sheds light on the organization of in vitro tubulin assemblies and paves the way towards a more comprehensive theory of in vivo systems, where the nonequilibrium effects resulting from the dynamic polymerization and deopolymerization of tubulin and thermal fluctuations conspire with the elastic forces described here.

We demonstrate a significantly simplified experimental approach for investigating liquid metallic hydrogen, which is crucial to understand the internal structure and evolution of giant planets. Plastic samples were shockcompressed and then probed by short pulses of X-rays generated by free electron lasers. By comparison with ab initio simulations, we provide indirect evidence for the creation of elemental hydrogen in shock-compressed plastics at $\sim 150\mathrm{GPa}$ and $\sim 5,000\mathrm{K}$ and thus in a regime where hydrogen is predicted to be metallic. Being the most common form of condensed matter in our solar system, and ostensibly the simplest of all elements, hydrogen is the model case for many theoretical studies and we provide a new possibility to benchmark models for conditions with extreme pressures and temperatures. Moreover, this approach will also allow to probe the chemical behavior of metallic hydrogen in mixture with other elements, which, besides its importance for planetary physics, may open up promising pathways for the synthesis of new materials.

Symmetries such as gauge invariance and anyonic symmetry play a crucial role in quantum many-body physics. We develop a general approach to constructing gauge-invariant or anyonic-symmetric autoregressive neural networks, including a wide range of architectures such as transformer and recurrent neural network, for quantum lattice models. These networks can be efficiently sampled and explicitly obey gauge symmetries or anyonic constraint. We prove that our methods can provide exact representation for the ground and excited states of the two- and three-dimensional toric codes, and the X-cube fracton model. We variationally optimize our symmetry-incorporated autoregressive neural networks for ground states as well as real-time dynamics for a variety of models. We simulate the dynamics and the ground states of the quantum link model of U(1) lattice gauge theory, obtain the phase diagram for the two-dimensional ${\mathbb{Z}}_2$ gauge theory, determine the phase transition and the central charge of the ${\text{SU(2)}}_3$ anyonic chain, and also compute the ground-state energy of the SU(2) invariant Heisenberg spin chain. Our approach provides powerful tools for exploring condensed-matter physics, high-energy physics, and quantum information science.

In the lower atmosphere of Earth, oxygen contains a higher fraction of the heavy ${}^{18}\mathrm{O}$ isotope than ocean water does (Dole effect). This isotopic enrichment is a signature of biological activity, set by the equilibrium between oxygenic photosynthesis and respiratory metabolisms in terrestrial and oceanic ecosystems. While the mixing between stratospheric and tropospheric oxygen leads to a slow isotopic homogenization, little is known about the isotopic oxygen enrichment in the mesosphere and thermosphere of Earth. In situ measurements from rocket-borne air samplers are limited to altitudes below the mesopause, while higher layers have only been accessible through the analysis of the oxidation of ancient cosmic spherules. Here we report the detection of the far-infrared fine-structure lines (${}^3{\mathrm{P}}_1\leftarrow {}^3{\mathrm{P}}_2$ and ${}^3{\mathrm{P}}_0\leftarrow {}^3{\mathrm{P}}_1$) of ${}^{18}\mathrm{O}$ in absorption against the Moon, and determine the ${}^{16}\mathrm{O}/{}^{18}\mathrm{O}$ ratio in atomic oxygen from the mesosphere and lower thermosphere in absorption. After correcting for isotopic exchange between atomic and molecular oxygen, our values for the bulk ${}^{16}\mathrm{O}/{}^{18}\mathrm{O}$ ratio of 468 and 382 in February and November 2021, respectively, fall significantly below that found in solar wind samples ($530\pm 2$), and encompass, within uncertainties, the corresponding ratios pertaining to the Dole effect in the troposphere (487), and those found in stratospheric ozone (429 to 466). We show that with existing technology, future, more sensitive measurements will allow us to monitor deviations from isotopic homogeneity in the mesosphere and lower thermosphere of Earth by remote sensing. We demonstrate that the collisional excitation of the fine-structure levels of the ${}^3\mathrm{P}$ ground-state triplet of ${}^{18}\mathrm{O}$ may compete with isotopic exchange reactions, implying a deviation from the Boltzmann distribution that would be established under local thermodynamic equilibrium.

Quantum cascade laser (QCL) frequency combs have revolutionized midinfrared (MIR) spectroscopy by their high brightness and fast temporal resolution, and are a promising technology for fully integrated and cost-effective sensors. As for other integrated comb sources such as microcombs and interband cascade lasers, QCLs have a comb spacing of several GHz, which is adequate for measurements of wide absorbing structures, typically found in liquid or solid samples. However, high-resolution gas-phase spectra require spectral interleaving and frequency calibration. We developed a frequency calibration scheme for fast interleaved measurements with combs featuring multi-GHz spacing. We then demonstrate dual-comb spectroscopy with a best accuracy of 600 kHz in single-shot 54 ms measurements spanning $40{\mathrm{cm}}^{-1}$ (1.2 THz) using QCLs at $7.8\mu \mathrm{m}\left(38.4\mathrm{THz}\right)$. This work paves the way for unambiguous and fast fingerprinting of complex molecular mixtures in the MIR with integrated comb sources.