Self-assembly is a fundamental concept in biology and of significant interest to nanotechnology. Significant progress has been made in characterizing and controlling the properties of the resulting structures, both experimentally and theoretically. However, much less is known about kinetic constraints and determinants of dynamical properties like time efficiency, although these constraints can become severe limiting factors of self-assembly processes. Here, we investigate how the time efficiency and other dynamical properties of reversible self-assembly depend on the morphology (shape) of the building blocks for systems in which the binding energy between the constituents is large. As paradigmatic examples, we stochastically simulate the self-assembly of constituents with triangular, square, and hexagonal morphology into two-dimensional structures of a specified size. We find that the constituents’ morphology critically determines the assembly time and how it scales with the size of the target structure. Our analysis reveals three key structural parameters defined by the morphology: the nucleation size and attachment order, which describe the effective order of the chemical reactions by which clusters nucleate and grow, respectively, and the growth exponent, which determines how the growth rate of an emerging structure scales with its size. Using this characterization, we formulate an effective theory of the self-assembly kinetics, which we show exhibits an inherent scale invariance. This allows us to identify general scaling laws that describe the minimal assembly time as a function of the size of the target structure. We show how these insights on the kinetics of self-assembly processes can be used to design assembly schemes that could significantly increase the time efficiency and robustness of artificial self-assembly processes.

In neural circuits, synaptic strengths influence neuronal activity by shaping network dynamics, and neuronal activity influences synaptic strengths through activity-dependent plasticity. Motivated by this fact, we study a recurrent-network model in which neuronal units and synaptic couplings are interacting dynamic variables, with couplings subject to Hebbian modification with decay around quenched random strengths. Rather than assigning a specific role to the plasticity, we use dynamical mean-field theory and other techniques to systematically characterize the neuronal-synaptic dynamics, revealing a rich phase diagram. Adding Hebbian plasticity slows activity in already chaotic networks and can induce chaos in otherwise quiescent networks. Anti-Hebbian plasticity quickens activity and produces an oscillatory component. Analysis of the Jacobian shows that Hebbian and anti-Hebbian plasticity push locally unstable modes toward the real and imaginary axes, respectively, explaining these behaviors. Both random-matrix and Lyapunov analysis show that strong Hebbian plasticity segregates network timescales into two bands, with a slow, synapse-dominated band driving the dynamics, suggesting a flipped view of the network as synapses connected by neurons. For increasing strength, Hebbian plasticity initially raises the complexity of the dynamics, measured by the maximum Lyapunov exponent and attractor dimension, but then decreases these metrics, likely due to the proliferation of stable fixed points. We compute the marginally stable spectra of such fixed points as well as their number, showing exponential growth with network size. Finally, in chaotic states with strong Hebbian plasticity, a stable fixed point of neuronal dynamics is destabilized by synaptic dynamics, allowing any neuronal state to be stored as a stable fixed point by halting the plasticity. This phase of freezable chaos offers a new mechanism for working memory.

Quantum error correction with erasure qubits promises significant advantages over standard error correction due to favorable thresholds for erasure errors. To realize this advantage in practice requires a qubit for which nearly all errors are such erasure errors, and the ability to check for erasure errors without dephasing the qubit. We demonstrate that a “dual-rail qubit” consisting of a pair of resonantly coupled transmons can form a highly coherent erasure qubit, where transmon $T_1$ errors are converted into erasure errors and residual dephasing is strongly suppressed, leading to millisecond-scale coherence within the qubit subspace. We show that single-qubit gates are limited primarily by erasure errors, with erasure probability $p_{\text{erasure}}=2.19(2)\times {10}^{-3}$ per gate while the residual errors are $\sim 40$ times lower. We further demonstrate midcircuit detection of erasure errors while introducing $<0.1\%$ dephasing error per check. Finally, we show that the suppression of transmon noise allows this dual-rail qubit to preserve high coherence over a broad tunable operating range, offering an improved capacity to avoid frequency collisions. This work establishes transmon-based dual-rail qubits as an attractive building block for hardware-efficient quantum error correction.

One of the tenets of molecular biology is that dynamic transitions between three-dimensional structures determine the function of proteins. Therefore, it seems only natural that evolutionary analysis of proteins, presently based mainly on their primary sequence, needs to shift its focus toward their function as assessed by corresponding structural transitions. This can be facilitated by recent progress in cryogenic electron microscopy that provides atomic structures of multiple conformational states for proteins and protein assemblies isolated from evolutionarily related species. In this work, we study evolutionary conservation of multiprotein assembly function by using mechanical strain as a quantitative footprint of structural transitions. We adopt the formalism of finite strain theory, developed in condensed matter physics, and apply it, as a case study, to a classical multiprotein assembly, the ATP synthase. Protein strain analysis provides a precise characterization of rotation domains that agrees with the present biophysical knowledge. In addition, we obtain a strain distribution on the protein structure associated with functional transitions. By analyzing in detail the strain patterns of the chains responsible for ATP synthesis across distinct species, we show that they are evolutionarily conserved for the same functional transition. Such conservation is not revealed by displacement or rotation patterns. Furthermore, within each functional transition, we can identify conserved strain patterns for ATP synthases isolated from different organisms. The observed strain conservation across evolutionary distant species indicates that strain should be essential in future structure-based evolutionary studies of protein function.

We synthesized polycrystalline ${\mathrm{La}}_3{\mathrm{Ni}}_2{\mathrm{O}}_{7-\delta }$ ($\delta \approx 0.07$) samples by using the sol-gel method without postannealing under high oxygen pressure, and then measured temperature-dependent resistivity under various hydrostatic pressures up to 18 GPa by using the cubic anvil and two-stage multianvil apparatus. We find that the density-wave-like anomaly in resistivity is progressively suppressed with increasing pressure and the resistivity drop corresponding to the onset of superconductivity emerges at pressure as low as $\sim 6\mathrm{GPa}$. Zero resistivity is achieved at 9 GPa below $T_{\mathrm{c}}^{\mathrm{zero}}\approx 6.6\mathrm{K}$, which increases quickly with pressure to 41 K at 18 GPa. However, the diamagnetic response was not detected in the ac magnetic susceptibility measurements up to 15 GPa, indicating a filamentary nature of the observed superconductivity in the studied pressure range. The constructed $T\text{−}P$ phase diagram reveals an intimate relationship between superconductivity, density-wave-like order, and the strange-metal-like behaviors. The observation of zero-resistance state in the polycrystalline ${\mathrm{La}}_3{\mathrm{Ni}}_2{\mathrm{O}}_{7-\delta }$ samples under high pressures not only corroborates the recent report of superconductivity in the pressurized ${\mathrm{La}}_3{\mathrm{Ni}}_2{\mathrm{O}}_7$ crystals but also facilitates further studies on this emerging family of nickelate high-$T_{\mathrm{c}}$ superconductors.

The ion-molecule reactions ${\mathrm{D}}_2^{+}+{\mathrm{NH}}_3$ and ${\mathrm{D}}_2^{+}+{\mathrm{ND}}_3$ are studied at low collision energies ($E_{\mathrm{coll}}$ from zero to approximately $k_B\times 50\mathrm{K}$), with the ${\mathrm{D}}_2^{+}$ ions in the ground rovibrational state and for different rotational temperatures of the ammonia molecules, using the Rydberg-Stark merged-beam approach. Two different rotational temperatures (approximately 15 K and approximately 40 K), measured by ($2+1$) resonance-enhanced multiphoton-ionization spectroscopy, are obtained by using a seeded supersonic expansion in He and a pure ammonia expansion, respectively. The experimental data reveal a strong enhancement of the rate coefficients at the lowest collision energies caused by the charge-dipole interaction. Calculations based on a rotationally adiabatic capture model accurately reproduce the observed kinetic-energy dependence of the rate coefficients. The rate coefficients increase with increasing rotational temperature of the ammonia molecules, which contradicts the expectation that rotational excitation should average the dipoles out. Moreover, these reactions exhibit a pronounced inverse kinetic isotope effect. The difference is caused by nuclear-spin-statistical factors and the smaller rotational constants and tunneling splittings in ${\mathrm{ND}}_3$.

We demonstrate the controlled spatiotemporal transfer of transverse orbital angular momentum (OAM) to electromagnetic waves: the spatiotemporal torquing of light. This is a radically different situation from OAM transfer to longitudinal, spatially defined OAM light by stationary or slowly varying refractive-index structures such as phase plates or air turbulence. We show that net transverse OAM per photon can be spatiotemporally imparted to a light pulse only if (1) a transient phase perturbation is well overlapped with the pulse in spacetime, or (2) the pulse initially has nonzero transverse OAM density, and the perturbation removes energy from it. Physical insight is provided by the mechanical analogy of torquing a wheel or removing mass as it spins. Our OAM theory for spatiotemporal optical vortex (STOV) pulses [S. W. Hancock et al.,Phys. Rev. Lett. 127, 193901 (2021)] correctly quantifies the light-matter interaction of our experiments and provides a spatiotemporal-torque-based explanation for the first measurement of STOVs [N. Jhajj et al., Phys. Rev. X 6, 031037 (2016)].

Active systems are composed of constituents with interactions that are generically nonreciprocal in nature. Such nonreciprocity often gives rise to situations where conflicting objectives exist, such as in the case of a predator pursuing its prey, while the prey attempts to evade capture. This situation is somewhat reminiscent of those encountered in geometrically frustrated systems where conflicting objectives also exist, which result in the absence of configurations that simultaneously minimize all interaction energies. In the latter, a rich variety of exotic phenomena are known to arise due to the presence of accidental degeneracy of ground states. Here, we establish a direct analogy between these two classes of systems. The analogy is based on the observation that nonreciprocally interacting systems with antisymmetric coupling and geometrically frustrated systems have in common that they both exhibit marginal orbits, which can be regarded as a dynamical system counterpart of accidentally degenerate ground states. The former is shown by proving a Liouville-type theorem. These “accidental degeneracies” of orbits are shown to often get “lifted” by stochastic noise or weak random disorder due to the emergent “entropic force” to give rise to a noise-induced spontaneous symmetry breaking, in a similar manner to the order-by-disorder phenomena known to occur in geometrically frustrated systems. Furthermore, we report numerical evidence of a nonreciprocity-induced spin-glass-like state that exhibits a short-ranged spatial correlation (with stretched exponential decay) and an algebraic temporal correlation associated with the aging effect. Our work establishes an unexpected connection between the physics of complex magnetic materials and nonreciprocal matter, offering a fresh and valuable perspective for comprehending the latter.

The deconfined quark-gluon plasma (QGP) created in relativistic heavy-ion collisions enables the exploration of the fundamental properties of matter under extreme conditions. Noncentral collisions can produce strong magnetic fields on the order of ${10}^{18}\mathrm{G}$, which offers a probe into the electrical conductivity of the QGP. In particular, quarks and antiquarks carry opposite charges and receive contrary electromagnetic forces that alter their momenta. This phenomenon can be manifested in the collective motion of final-state particles, specifically in the rapidity-odd directed flow, denoted as $v_1(\mathsf{y})$. Here, we present the charge-dependent measurements of $d{v}_1/d\mathsf{y}$ near midrapidities for ${\pi }^{\pm }$, $K^{\pm }$, and $p(\overline{p})$ in $\mathrm{Au}+\mathrm{Au}$ and isobar (${}_{44}{}^{96}\mathrm{Ru}+{}_{44}{}^{96}\mathrm{Ru}$ and ${}_{40}{}^{96}\mathrm{Zr}+{}_{40}{}^{96}\mathrm{Zr}$) collisions at $\sqrt{s_{\mathrm{NN}}}=200\mathrm{GeV}$, and in $\mathrm{Au}+\mathrm{Au}$ collisions at 27 GeV, recorded by the STAR detector at the Relativistic Heavy Ion Collider. The combined dependence of the $v_1$ signal on collision system, particle species, and collision centrality can be qualitatively and semiquantitatively understood as several effects on constituent quarks. While the results in central events can be explained by the $u$ and $d$ quarks transported from initial-state nuclei, those in peripheral events reveal the impacts of the electromagnetic field on the QGP. Our data put valuable constraints on the electrical conductivity of the QGP in theoretical calculations.

Thermally activated energy-barrier crossing is ubiquitous in physical, chemical, and biological processes. Most barrier-crossing attempts have insufficient energy to overcome the barrier; hence, productive transition paths that successfully cross the barrier are very rare compared to nonproductive fluctuations that enter the barrier region but return without crossing it. Recent experimental advances have yielded important insights into transition paths, but nonproductive attempts remain little studied experimentally or theoretically, even though they can reveal information about parts of the reaction energy landscape not visited during transition paths. Observing the diffusive dynamics of a bead hopping between bistable optical traps as a model system, we measured the duration, maximum position along the reaction coordinate, and occupancy statistics of unsuccessful crossing attempts. Experimental results agreed quantitatively with expectations of an analytical framework we derived from committor theory. Applying these analyses to a more complex example, DNA hairpin folding under tension, we found that some properties differed from those of transition paths, such as the asymmetric occupancies for folding and unfolding attempts, whereas others were similar, such as the diffusion coefficient reflecting landscape roughness. These results show how nonproductive crossing attempts can be detected and analyzed rigorously, enabling characterization of the full dynamics within the transition region.

Allometric relations between two observables are a widespread phenomenon in biology. The volume of nuclei, for example, has frequently been reported to scale linearly with cell volume, $V_N\sim V_C$, but conflicting, sublinear power-law correlations have also been found. Given that nuclei are vital organelles that harbor and maintain the DNA of cells, an understanding of allometric nuclear volumes that ultimately define the concentration and accessibility of chromatin is of great interest. Using the model organism Caenorhabditis elegans, we show here that the allometry of nuclei is a dynamically adapting phenomenon; i.e., we find $V_N\sim V_C^{\alpha }$ with a time-dependent scaling exponent $\alpha$ (“dynamic allometry”). This finding is due to relaxation growth of nuclear volumes at a rate that scales with cell size. If cell division stops the relaxation of nuclei in a premature stage, $\alpha <1$ is observed, whereas completion of relaxation yields $\alpha =1$ (“isometry”). Our experimental data are well captured by a simple and supposedly generic model in which nuclear size is determined by the available membrane area that can be integrated into the nuclear envelope to relax the expansion pressure from decondensed chromatin. Extrapolation of our results to growing and proliferating cells suggests that isometric scaling of cell and nuclear volumes is the generic case.

Strong laser pulses enable probing molecules with their own electrons. The oscillating electric field tears electrons off a molecule, accelerates them, and drives them back toward their parent ion within a few femtoseconds. The electrons are then diffracted by the molecular potential, encoding its structure and dynamics with angstrom and attosecond resolutions. Using elliptically polarized laser pulses, we show that laser-induced electron diffraction is sensitive to the chirality of the target. The field selectively ionizes molecules of a given orientation and drives the electrons along different sets of trajectories, leading them to recollide from different directions. Depending on the handedness of the molecule, the electrons are preferentially diffracted forward or backward along the light propagation axis. This asymmetry, reaching several percent, can be reversed for electrons recolliding from two ends of the molecule. The chiral sensitivity of laser-induced electron diffraction opens a new path to resolve ultrafast chiral dynamics.

Active constituents burn fuel to sustain individual motion, giving rise to collective effects that are not seen in systems at thermal equilibrium, such as phase separation with purely repulsive interactions. There is a great potential in harnessing the striking phenomenology of active matter to build novel controllable and responsive materials that surpass passive ones. Yet, we currently lack a systematic roadmap to predict the protocols driving active systems between different states in a way that is thermodynamically optimal. Equilibrium thermodynamics is an inadequate foundation to this end, due to the dissipation rate arising from the constant fuel consumption in active matter. Here, we derive and implement a versatile framework for the thermodynamic control of active matter. Combining recent developments in stochastic thermodynamics and response theory, our approach shows how to find the optimal control for either continuous- or discrete-state active systems operating out of equilibrium. Our results open the door to designing novel active materials that are not only built to stabilize specific nonequilibrium collective states but are also optimized to switch between different states at minimum dissipation.

We experimentally demonstrate a microwave photon-multiplication scheme which combines the advantages of a single-photon detector and a power meter by multiplying the incoming photon number by an integer factor. Our first experimental implementation achieves an $n=3$-fold multiplication with 0.69 efficiency in a 116 MHz bandwidth up to an input photon rate of 400 MHz. It loses phase information but does not require any dead time or time binning. We expect an optimized device cascading such multipliers to achieve number-resolving measurement of itinerant photons with low dark count, which would offer new possibilities in a wide range of quantum-sensing and quantum-computing applications.

Owing to their strong dipole moment and long coherence times, superconducting qubits have demonstrated remarkable success in hybrid quantum circuits. However, most qubit architectures are limited to the GHz frequency range, severely constraining the class of systems they can interact with. The fluxonium qubit, on the other hand, can be biased to very low frequency while being manipulated and read out with standard microwave techniques. Here, we design and operate a heavy fluxonium with an unprecedentedly low transition frequency of 1.8 MHz. We demonstrate resolved sideband cooling of the “hot” qubit transition with a final ground state population of 97.7%, corresponding to an effective temperature of $23\mathrm{\mu }\mathrm{K}$. We further demonstrate coherent manipulation with coherence times $T_1=34\mathrm{\mu }\mathrm{s}$, $T_2^{*}=39\mathrm{\mu }\mathrm{s}$, and single-shot readout of the qubit state. Importantly, by directly addressing the qubit transition with a capacitively coupled waveguide, we showcase its high sensitivity to a radio-frequency field. Through cyclic qubit preparation and interrogation, we transform this low-frequency fluxonium qubit into a frequency-resolved charge sensor. This method results in a charge sensitivity of $33\mathrm{\mu }\mathrm{e}/\sqrt{\mathrm{Hz}}$, or an energy sensitivity (in joules per hertz) of $2.8\hslash$. This method rivals state-of-the-art transport-based devices, while maintaining inherent insensitivity to dc-charge noise. The high charge sensitivity combined with large capacitive shunt unlocks new avenues for exploring quantum phenomena in the 1–10 MHz range, such as the strong-coupling regime with a resonant macroscopic mechanical resonator.

Moiré materials provide fertile ground for the correlated and topological quantum phenomena. Among them, the quantum anomalous Hall (QAH) effect, in which the Hall resistance is quantized even under zero magnetic field, is a direct manifestation of the intrinsic topological properties of a material and an appealing attribute for low-power electronics applications. The QAH effect has been observed in both graphene and transition metal dichalcogenide (TMD) moiré materials. It is thought to arise from the interaction-driven valley polarization of the narrow moiré bands. Here, we show that the newly discovered QAH state in AB-stacked ${\mathrm{MoTe}}_2/{\mathrm{W}\mathrm{S}\mathrm{e}}_2$ moiré bilayers is not valley polarized but valley coherent. The layer- and helicity-resolved optical spectroscopy measurement reveals that the QAH ground state possesses spontaneous spin (valley) polarization aligned (antialigned) in two TMD layers. In addition, saturation of the out-of-plane spin polarization in both layers occurs only under high magnetic fields, supporting a canted spin texture. Our results call for a new mechanism for the QAH effect and highlight the potential of TMD moiré materials with strong electronic correlations and spin-orbit interactions for exotic topological states.

Soap bubbles are simple, yet very unique and marvelous objects. They exhibit a number of interesting properties such as beautiful interference colors and the formation of minimal surfaces. Various optical phenomena have been studied in soap films and bubbles, but so far they have not been employed as optical cavities. Here we demonstrate that dye doped soap or smectic liquid crystal bubbles can support whispering gallery mode lasing, which is observed in the spectrum as hundreds of regularly spaced peaks, resembling a frequency comb. The lasing enabled the measurement of size changes as small as 10 nm in a millimeter-sized, $\sim 100\text{−}\mathrm{nm}$-thick bubble. Bubble lasers were used as extremely sensitive electric field sensors with a smallest measurable electric field of $110{\mathrm{Vm}}^{-1}{\mathrm{Hz}}^{-1/2}$. They also enable the measurement of pressures up to a 100 bar with a resolution of 1.5 Pa, resulting in a dynamic range of almost ${10}^7$. By connecting the bubble to a reservoir of air, almost arbitrarily low pressure changes can be measured while maintaining an outstanding dynamic range. The demonstrated soap bubble lasers are a very unique type of microcavities which are one of the best electric field and pressure microsensors to date and could in the future also be employed to study thin films and cavity optomechanics.

After two decades of measurements, neutrino physics is now advancing into the precision era. With the long-baseline experiments designed to tackle current open questions, a new query arises: Can atmospheric neutrino experiments also play a role? To that end, we analyze the expected sensitivity of current and near-future water(ice)-Cherenkov atmospheric neutrino experiments in the context of standard three-flavor neutrino oscillations. In this first in-depth combined atmospheric neutrino analysis, we analyze the current shared systematic uncertainties arising from the common flux and neutrino-water interactions. We then implement the systematic uncertainties of each experiment in detail and develop the atmospheric neutrino simulations for Super-Kamiokande, with and without neutron-tagging capabilities, IceCube Upgrade, ORCA, and Hyper-Kamiokande detectors. We carefully review the synergies and features of these experiments to examine the potential of a joint analysis of these atmospheric neutrino data in resolving the ${\theta }_{23}$ octant at 99% confidence level (CL), and determining the neutrino mass ordering above $5\sigma$ by 2030. Additionally, we assess the capability to constrain ${\theta }_{13}$ and the $CP$-violating phase (${\delta }_{CP}$) in the leptonic sector independently from reactor and accelerator neutrino data. A combination of the atmospheric neutrino measurements will enhance the sensitivity to a greater extent than the simple sum of individual experiment results reaching more than $3\sigma$ for some values of ${\delta }_{CP}$. These results will provide vital information for next-generation accelerator neutrino oscillation experiments such as DUNE and Hyper-Kamiokande.

Individuals involved in common group activities or settings, e.g., college students that are enrolled in the same class and/or live in the same dorm, are exposed to recurrent contacts of physical proximity. These contacts are known to mediate the spread of an infectious disease; however, it is not obvious how the properties of the spreading process are determined by the structure of and the interrelation among the group settings that are at the root of those recurrent interactions. Here, we show that reshaping the organization of groups within a population can be used as an effective strategy to decrease the severity of an epidemic. Specifically, we show that when group structures are sufficiently correlated, e.g., the likelihood for two students living in the same dorm to attend the same class is sufficiently high, outbreaks are longer but milder than for uncorrelated group structures. Also, we show that the effectiveness of interventions for disease containment increases as the correlation among group structures increases. We demonstrate the practical relevance of our findings by taking advantage of data about housing and attendance of students at the Indiana University campus in Bloomington. By appropriately optimizing the assignment of students to dorms based on their enrollment, we are able to observe a twofold to fivefold reduction in the severity of simulated epidemic processes.

Large interacting systems in biology often exhibit emergent dynamics, such as coexistence of multiple timescales, manifested by fat tails in the distribution of waiting times. While existing tools in statistical inference, such as maximum entropy models, reproduce the empirical steady-state distributions, it remains challenging to learn dynamical models. We present a novel inference method, called generalized Glauber dynamics. Constructed through a non-Markovian fluctuation dissipation theorem, generalized Glauber dynamics tunes the dynamics of an interacting system, while keeping the steady-state distribution fixed. We motivate the need for the method on real data from Eco-HAB, an automated habitat for testing behavior in groups of mice under seminaturalistic conditions, and present it on simple Ising spin systems. We show its applicability for experimental data by inferring dynamical models of social interactions in a group of mice that reproduce both its collective behavior and the long tails observed in individual dynamics.