A swimming microorganism stirs the surrounding fluid, creating a flow field that governs not only its locomotion and nutrient uptake, but also its interactions with other microorganisms and the environment. Despite its fundamental importance, capturing this flow field and unraveling its biological implications remains a challenge. Here, we report direct, time-resolved measurements of the three-dimensional (3D) flow field generated by a single, free-swimming microalga, Chlamydomonas reinhardtii, a model organism for microbial locomotion and flagellar dynamics. Supported by hydrodynamic modeling and simulations, our measurements resolve how established two-dimensional (2D) flow features such as in-plane vortices and the stagnation point emerge from and shape the full algal flow in 3D. Moreover, we reveal unexpected low-Reynolds-number flow phenomena including micron-sized vortex rings and periodically recurring translating vortices and uncover topological changes in the underlying flow structure associated with the puller-to-pusher transition of an alga. Biologically, access to the 3D flow field enables rigorous quantification of the alga’s energy expenditure, as well as its swimming and feeding efficiency, improving the precision of these physiological metrics. Taken together, our study demonstrates rich vortex dynamics in inertialess flows and shows their influence on microbial motility. The work also introduces an experimental method for mapping the fluid environment sculpted by beating flagella.

“Hidden” phases, generated using ultrafast laser pulses (few hundred femtoseconds), with distinct properties than at the thermodynamic equilibrium, are appealing for technologies, as they can be long-lived, with a lifetime of hours or weeks, and reversible with temperature sweeping or extra pulses. In this regard, ${\mathrm{La}}_{2/3}{\mathrm{Ca}}_{1/3}{\mathrm{MnO}}_3$ (LCMO) stands out due to its tunability through epitaxial strain, which can drive the bulk ferromagnetic metal into an antiferromagnetic insulator (AFI), and its susceptibility to photoinduced transitions. Indeed, AFI LCMO displays a long-lived photoinduced transition into a putative hidden phase whose exact nature and excitations are still largely unknown. Here, we combine ultrafast photoexcitation in the near infrared with in situ transport, x-ray absorption, and resonant inelastic x-ray scattering (RIXS) to investigate the excitations (polarons, phonons, and orbital) of the photoexcited phase of LCMO and contrast them with the thermodynamic phases achieved through strain and temperature. In the thermodynamic regime, we establish the correlation between polarons and transport placing them in the “strong coupling” regime of the Holstein model. Upon photoexcitation of LCMO-AFI, we uncover a long-lived phase characterized by the softening of the polaron excitations, the partial suppression of the Jahn-Teller distortion, and nearly unchanged phonons, showing the emergence of a photoexcited state absent in the equilibrium phase diagram. Finally, by varying temperature, epitaxial strain, and photoexcitation fluence, we construct a polaron phase diagram and identify the key spectroscopic signatures of each phase. Our laser-RIXS approach establishes a versatile platform for exploring photoinduced hidden phases in quantum materials in nonstroboscopic conditions.

One of the premier utilities of present-day noisy quantum computers is simulation of many-body quantum systems. We study how long in time is such a discrete-time simulation representative of a continuous time Hamiltonian evolution; namely, a finite time step introduces so-called Trotterization errors. We demonstrate that the truncated operator propagator (Ruelle-Pollicott resonances) is a powerful tool to that end, as well as to study prethermalization and discrete-time crystals, including finding those phenomena at large gate duration. We show that the effective energy is more stable than suggested by Trotter errors—a manifestation of prethermalization—while all other observables are not. Even the most stable observable though deteriorates in the thermodynamic limit. Different than in classical systems with the strongest chaos, where the faithfulness time (the shadowing time) can be infinite, in quantum many-body chaotic systems it is finite. A corollary of our results is also that, opposite of previous claims, there is no Trotterization transition in nonintegrable many-body quantum systems. We demonstrate our results on a one-dimensional (1D) kicked Ising model, as well as on a 1D kicked XX model and a 2D kicked Ising model. The truncated propagator is also used to calculate the energy diffusion constant in the tilted-field Ising model with high accuracy.

We use high-resolution chemical potential measurements to extract the entropy of monolayer and bilayer graphene in the quantum Hall regime via the Maxwell relation $[(d\mu )/(dT)]{|}_N=-[(dS)/(dN)]{|}_T$. Measuring the entropy from $T=300\mathrm{K}$ down to $T=200\mathrm{mK}$, we identify the sequential emergence of quantum Hall ferromagnetism, fractional quantum Hall states, and various charge orders by comparing the measured entropy in different temperature regimes with theoretical models. At the lowest temperature of $T\approx 200\mathrm{mK}$ we perform a detailed study of the entropy near even-denominator fractional quantum Hall states in bilayer graphene, and comment on the possible topological origin of the observed excess entropy.

Model order reduction encompasses mathematical techniques aimed at reducing the complexity of mathematical models in simulations while retaining the essential characteristics and behaviors of the original model. This is particularly useful in the context of large-scale dynamical systems, which can be computationally expensive to analyze and simulate. Here, we present a model order reduction technique to reduce the time complexity of open quantum systems, grounded in the principle of measurement-adapted coarse graining. This method, governed by a coarse-graining timescale $\tau$ and the spectral band center ${\omega }_0$ of the measurement channel, organizes corrections to the lowest-order model which aligns with the rotating-wave approximation Hamiltonian in certain limits and rigorously justifies the resulting effective quantum master equation (EQME). The focus on calculating to a high degree of accuracy what can only be resolved by the measurement introduces a principled regularization procedure to address singularities and generates low-stiffness models suitable for efficient long-time integration. The closed-form EQME parameters greatly enhance interpretability, while the predicted EQME structure provides a foundation for deriving stochastic master equations under continuous measurement and for constructing efficient gray-box models for system identification and control. As a demonstration, we derive the fourth-order EQME for a challenging problem related to the dynamics of a superconducting qubit under high-power dispersive readout in the presence of a continuum of dissipative waveguide modes. This derivation shows that the lowest-order terms align with previous results, while higher-order corrections suggest new phenomena.

The preparation of high-fidelity non-Clifford (magic) states is an essential subroutine for universal quantum computation but imposes substantial space-time overhead. Magic-state factories based on high-rate and -distance quantum low-density parity-check (LDPC) codes equipped with transversal non-Clifford gates can potentially reduce these overheads significantly, by circumventing the need for multiple rounds of distillation and by producing a large number of magic states in a single code block. As a step toward realizing efficient, fault-tolerant magic-state production, we introduce a class of finite block-length quantum LDPC codes which we name tricycle codes, generalizing the well-known bicycle codes to three homological dimensions. These codes can support constant-depth physical circuits that implement logical $CCZ$ gates between three code blocks. To construct these constant-depth $CCZ$ circuits, we develop analytical and numerical techniques that apply to a broad class of three-dimensional homological and balanced-product codes. We further show that tricycle codes enable single-shot state preparation and error correction, leading to a highly efficient magic-state generation protocol. Numerical simulations of specific codes confirm robust performance under circuit-level noise, demonstrating a high circuit-noise threshold of $>0.5\%$. With modest postselection, certain tricycle codes of block lengths of only approximately 50–100 qubits are shown to produce $|\overline{CCZ}⟩$ magic states with logical error rates ranging from $2\times {10}^{-8}$ to below $3\times {10}^{-11}$. Finally, we construct optimal depth syndrome extraction circuits for tricycle codes and present a protocol for implementing them efficiently on a reconfigurable neutral-atom platform.

Quantum thermodynamics addresses the dynamics of heat flow in quantum devices driven out of equilibrium. Although mesoscopic circuits at low temperatures provide a flexible platform to explore this dynamics, experimental studies are wanting, because thermal timescales in nanodevices are often too fast. Here, we engineer and investigate with noise thermometry a mesoscopic thermal circuit where heat flows between electron, phonon, and nuclear systems can occur on slower timescales. The central constituent of this device is a micrometer-scale metallic island electrically connected to large cold electron reservoirs through two to four ballistic quantum Hall channels, a component frequently used for exploring stationary thermal currents. We uncover a two-step thermalization process specific to the mesoscopic scale, involving a fast initial temperature step followed by a much slower rise extending over minutes. This observation is quantitatively accounted for by the balance between heat flows through electronic quantum channels, to cold phonons, and to the nuclear spins in the metallic island. The disclosed mesoscopic thermalization takes a step into the field of quantum thermodynamical phenomena, highlighting their distinctive nature on a central constituent of quantum circuits. The implications for the thermal engineering of nanodevices include the thermal characterization of exotic states at high magnetic field.

A remarkable feat of active matter physics is that systems as diverse as collections of self-propelled particles, nematics mixed with molecular motors, and interacting robots can all be described by symmetry-based continuum theories. These descriptions rely on reducing complex effects of individual motors to a few key active parameters, which increase with activity. Here we observe a striking anomaly in the continuum description of nonreciprocal active solids, a ubiquitous class of active materials. Using a combination of metamaterial experiments and coarse-graining theory we find that as microscopic activity increases, macroscale active response can vanish: more is less. In this highly active regime, nonaffine and localized modes prevail and destroy the large-scale signature of microscopic activity. These modes exist in any dilute periodic structure and emerge in random lattices below a percolation transition. Our results unveil a counterintuitive facet of active matter, offering new principles for engineering materials far from equilibrium.

In thermoelectric (TE) and other functional electronic materials, chemical doping is commonly employed to tune the carrier density toward an optimal Fermi level and, in turn, maximize the electrical transport. However, in some systems, such as the emerging high-performance $p$-type TE material $\alpha$-MgAgSb, chemical doping is challenging due to its weak chemical bonds and extremely low solubility of heteroatomic dopants, which makes it difficult to increase the hole carrier density and realize the otherwise predictable improvements in the TE power factor. Here, we report a doping-free strategy to enhance the TE performance of $\alpha$-MgAgSb by utilizing a phase-transition-induced self-doping process. Annealing at the phase-transition temperature of 593 K lowers the formation energy of Ag vacancies in the high-temperature $\beta$ phase, and these vacancies are subsequently retained upon cooling back to the $\alpha$ phase. As a result, the hole concentration increases markedly from $4.5\times {10}^{19}$ to $1.3\times {10}^{20}{\mathrm{cm}}^{-3}$, activating multiple valence bands and boosting the room-temperature power factor by $\sim 35\%$ to $30\mathrm{\mu }\mathrm{W}{\mathrm{cm}}^{-1}{\mathrm{K}}^{-2}$. A single-leg device fabricated from the optimized material achieves a high conversion efficiency of 10.7% and a maximum output power of 71.1 mW at $\mathrm{\Delta }T=285\mathrm{K}$. This work demonstrates a viable pathway for enhancing TE performance via phase-transition engineering.

Diamond, an archetype of hardness and brittleness, can nonetheless display striking elastic compliance at the nanoscale, in sharp contrast to its ultrastiff, fracture prone bulk behavior. Despite recent experimental progress, the atomic scale origin of this anomalous elasticity remains unresolved. Here, we uncover a pronounced size- dependent softening in nanodiamond, with the effective axial Young’s modulus decreasing from about 1000 to about 700 GPa as the particle diameter shrinks from 13 to 4 nm. By integrating in situ transmission electron microscopy nanomechanical testing with first principles calculations and molecular dynamics simulations, we show that this stiffness reduction does not arise from the surface atomic layers, which remain comparatively stiff, but instead from weakened bonding in a distinct interfacial region between the surface and the crystalline core. These under-coordinated regions localize strain and accommodate large elastic deformation. The results uncover a previously overlooked interfacial mechanism that governs elasticity in brittle nanomaterials and offer design principles for nanomechanical resonators, quantum devices, and thermal transport applications with tunable stiffness.

The genome contains genetic information essential for a cell’s life. The genome’s spatial organization inside the cell nucleus is critical for its proper function including gene regulation. The two major genomic compartments, euchromatin and heterochromatin, contain largely transcriptionally active and silenced genes, respectively, and exhibit distinct dynamics. In this work, we present a hydrodynamic framework that describes the large-scale behavior of euchromatin and heterochromatin and accounts for the interplay of mechanical forces, active processes, and nuclear confinement. Our model shows contractile stresses from cross-linking proteins lead to the formation of heterochromatin droplets via mechanically driven phase separation. These droplets grow, coalesce, and, in nuclear confinement, wet the boundary. Active processes, such as gene transcription in euchromatin, introduce nonequilibrium fluctuations that drive long-range, coherent motions of chromatin as well as the nucleoplasm and, thus, alter the genome’s spatial organization. These fluctuations also indirectly deform heterochromatin droplets, by continuously changing their shape. Taken together, our findings reveal how active forces, mechanical stresses, and hydrodynamic flows contribute to the genome’s organization at large scales and provide a physical framework for understanding chromatin organization and dynamics in live cells.

Evidence of superconductivity has recently been reported in pressurized nickelates, providing a new platform to explore high-temperature superconductivity. However, detailed experimental characterization of the superconducting properties of nickelates under pressure remains limited and technically challenging. Here, we report the first full temperature-dependent measurements of the upper critical field (${\mu }_0{H}_{c2}$) in pressurized trilayer nickelate ${\mathrm{La}}_4{\mathrm{Ni}}_3{\mathrm{O}}_{10-\delta }$ single crystal, achieved by integrating advanced high-magnetic-field and high-pressure techniques. Remarkably, ${\mathrm{La}}_4{\mathrm{Ni}}_3{\mathrm{O}}_{10-\delta }$ exhibits nearly isotropic superconductivity, with the anisotropic parameter $\gamma$ decreasing monotonically from 1.4 near $T_c$ to 1 at lower temperatures. By applying a two-band model analysis out of plane and in plane ${\mu }_0{H}_{c2}$, we uncover a compensation of anisotropic diffusivity between bands primarily originating from $d_{z^2}$ and $d_{x^2-y^2}$ orbitals, resulting in an exceptionally isotropic superconducting characteristic. These findings indicate the significant contribution of the $d_{z^2}$ orbital to superconductivity in pressurized ${\mathrm{La}}_4{\mathrm{Ni}}_3{\mathrm{O}}_{10-\delta }$ and provide essential constraints for theoretical models of the pairing mechanism in Ruddlesden-Popper nickelates.

Models of complex dynamical systems like the Earth’s climate often involve large numbers of uncertain parameters. Comprehensive exploration of the parameter space is typically prohibitive due to excessive computational costs, and systematic gradient-based parameter optimization is not feasible because such models are typically not differentiable. This is especially problematic in cases where the models intend to describe highly nonlinear and possibly abrupt dynamics, where sensitivity to parameter changes is high. Components of Earth’s climate system, such as the North Atlantic Overturning Circulation, the polar ice sheets, or the Amazon rainforest, are at risk of undergoing critical transitions in response to anthropogenic climate change. However, estimates of the critical forcing thresholds are highly uncertain because the parameter spaces of complex climate models cannot be fully explored. Concerns have been raised that the above Earth system components are too stable in state-of-the-art models. Here, we introduce a method for efficient, systematic, and objective calibration of dynamical complex system models, targeted at adjusting system stability. Given a number of physical or observational constraints, our method moves the system in a direction where the system loses or gains stability, guided by indicators of “critical slowing down”. In contrast to a brute force approach, where the computational cost would exponentially increase with the number of parameters, our method scales polynomially and thus evades the curse of dimensionality. We successfully apply our method to a conceptual double-fold bifurcation model and a physically plausible reduced-order model of the global ocean circulation. Our method can efficiently adjust stability biases across a range of complex system models, helping to reveal hidden instabilities and resulting state transitions they induce. In particular, it can help us to explore and improve the representation of key multistable components of the Earth system in climate models.

Considerable effort continues to be devoted to the exploration of next-generation high-$\kappa$ materials that combine a high dielectric constant with a wide band gap. However, machine learning (ML)-based virtual screening has remained challenging, primarily due to the low accuracy in predicting the ionic contribution to the dielectric tensor, which dominates the dielectric performance of high-$\kappa$ materials. We propose a joint ML model that predicts Born effective charges using an equivariant graph neural network, and phonon properties using a highly accurate pretrained ML potential. The ionic dielectric tensor is then computed analytically from these quantities. This approach significantly improves the accuracy of ionic contribution. Using the proposed model, we successfully identified 31 novel high-$\kappa$ oxides from a screening pool of over 8000 candidates.

Nonlinear phenomena underpin a broad array of technologies, from electronic frequency mixers and harmonic generation to parametric amplification and optical frequency doubling. Conventional schemes for generating microwave frequency combs are constrained by intrinsic material or junction properties that require high driving powers. Here, we overcome these limitations via phase-transition physics. We show that a hybrid quantum system—composed of a solid-state spin ensemble and a nonlinear oscillator—exhibits a distinct bistable phase transition point (BP) where system response becomes both highly enhanced and nonlinear. The nonlinearity around the BP is higher order than other phase transitions, such as exceptional points, critically producing high-order frequency response which enhances nonlinear processes. Approaching the BP, we demonstrate a frequency comb with a record number of teeth at unprecedentedly low driving powers, surpassing previous results using magnonic systems and traditional diode-based approaches. These findings highlight the potential of hybrid quantum systems in advancing high-performance frequency manipulation.

Electromagnetic fields induce electronic transitions, generate currents, and fundamentally alter quantum states of matter through strong light-matter interactions. As one established route, Floquet engineering provides a powerful framework to dress electronic states with time-periodic fields, giving rise to quasistationary Floquet states. With increasing field strength, nonperturbative responses of the dressed states emerge, yet their nonlinear dynamics remain challenging to interpret. In this work, we explore the emergence of nonadiabatic Landau-Zener transitions among Floquet states in Cu(111) under intense optical fields. With increasing field strength, we reveal a transition from perturbative dressing to a regime where nonadiabatic tunneling among Floquet states dominate the electronic dynamics. These insights are obtained through interferometrically time-resolved multiphoton photoemission spectroscopy, which serves as a sensitive probe of transient Floquet state dynamics. Numerical simulations and the theory of instantaneous Floquet states allow us to directly examine real-time excitation pathways in this nonperturbative photoemission regime. Our results clarify different light-dressing regimes in materials and provide microscopic insight relevant to ultrafast light wave electronics.

Traveling-wave parametric amplifiers (TWPAs) have attracted much attention for their broadband amplification and near-quantum-limited noise performance. TWPAs are nonreciprocal by nature providing gain for forward-propagating signals and transmission line losses for backward traveling waves. This intrinsic nonreciprocity is insufficient to protect sensitive quantum devices from backaction due to noise from warmer amplification stages in practical systems, and requires the use of bulky cryogenic isolators. We present a multistage TWPA (mTWPA) that addresses this limitation by achieving passive in-band reverse isolation alongside near-quantum-limited noise performance. The multistage architecture consists of two mode conversion stages and a reflectionless high-pass filter that provides the passive isolation. Experimental measurements of a prototype mTWPA demonstrated 20 dB of forward gain across a 1.6 GHz bandwidth and greater than 35 dB of reverse isolation. Noise measurements indicate performance at 1.7 times the quantum limit. This demonstrates that the increased complexity of a multistage TWPA design does not lead to significant added noise. The designed distribution of gain across the stages is engineered to minimize internal amplifier noise at the input, and we propose further optimization strategies in redistribution of the gain between the stages. This level of isolation mitigates noise from warmer amplification stages, matching the performance of conventional isolators. The passive reverse isolation of the mTWPA, allows for the amplifier to operate in pulsed mode where the amplifier is off during qubit gate operations and is turned on during readout allowing for an isolator free scalable readout architecture.

Quantum measurements affect the state of the observed systems via backaction. While projective measurements extract maximal classical information, they drastically alter the system. In contrast, indirect measurements balance information extraction with the degree of disturbance. Considering the prevalent use of projective measurements in quantum computing and communication protocols, the potential benefits of indirect measurements in these fields remain largely unexplored. In this work, we show that measurement backaction, a purely quantum effect, can be harnessed within the quantum reservoir computing framework to enhance temporal data processing. Incorporating indirect measurements leads to improved execution-time scaling and overall performance. Our results reveal that carefully optimizing the measurement strength can significantly improve the quantum reservoir computing algorithm performance. Furthermore, our approach demonstrates improved memory performance when compared with state-of-the-art classical-feedback protocols. This work provides a comprehensive and practical recipe to promote the implementation of indirect-measurement-based protocols in quantum reservoir computing. Moreover, our findings motivate further exploration of experimental protocols that leverage the backaction effects of indirect measurements.

Collisions between ultracold calcium monohydroxide (CaOH) molecules are realized and studied. Inelastic collision rate constants are measured for CaOH prepared in ground and excited vibrational states, and the electric field dependence of these rates is measured for molecules in single quantum states of the parity-doubled bending mode. Theoretical calculations of collision rate coefficients are performed and found to agree with measured values. The lowest collisional loss rates are for states with repulsive long-range potentials that shield ultracold molecules from loss channels at short distance. These results unveil the collisional behavior of parity-doublet molecules in the ultracold regime and lay the foundation for future experiments to evaporatively cool polyatomic molecules to quantum degeneracy.

The restricted Boltzmann machine (RBM) is a neural network based on the Ising model, well known for its ability to learn probability distributions and stochastically generate new content. However, the high computational cost of Gibbs sampling in content generation tasks imposes significant bottlenecks on electronic implementations. Here, we propose a photonic restricted Boltzmann machine (PRBM) that leverages photonic computing to accelerate Gibbs sampling, enabling efficient content generation. By introducing an efficient encoding method, the PRBM eliminates the need for computationally intensive matrix decomposition and reduces the computational complexity of a single dot product in Gibbs sampling from $O(N)$ to $O(1)$. Moreover, with the advantage of photonic computation of non–von Neumann computing architecture, we physically encode the model parameters onto the phases of different wavelength light fields on a spatial light modulator, substantially enhancing computation efficiency for large-scale RBMs. We experimentally validate the photonic-accelerated Gibbs sampling by simulating a two-dimensional Ising model, where the observed phase transition temperature closely matches the theoretical predictions. Beyond physics-inspired tasks, the PRBM demonstrates strong performance in generating and restoring diverse content, including images and temporal sequences. The scalability and reduced training cost of the PRBM framework underscore its potential as a promising pathway for advancing photonic computing in generative artificial intelligence.