We identify quantum imaginary time evolution as a Riemannian gradient flow on the unitary group. We develop an upper bound for the error between the two evolutions that can be controlled through the step size of the Riemannian gradient descent that minimizes the energy of the system. We discuss implementations through adaptive quantum algorithms and present a stochastic Riemannian gradient descent algorithm in which each step is efficiently implementable on a quantum computer. We prove that for a sufficiently small step size, the stochastic evolution concentrates around the imaginary time evolution, thereby providing performance guarantees for cooling the system through stochastic Riemannian gradient descent. Finally, we show that Riemannian gradient descent can be understood as an approximation to quantum imaginary time evolution that does not employ classical optimization.

The emergent practical applicability of the Quantum Approximate Optimization Algorithm (QAOA) for approximate combinatorial optimization is a subject of considerable interest. One of the primary limitations of QAOA is the task of finding a set of good parameters, which is usually done using a variational optimization loop. Parameter transfer, or parameter concentration, is a phenomenon where QAOA angles trained on problem instances that are self-similar tend to perform well for other problem instances from that similar class. This suggests a potentially highly efficient and scalable nonvariational learning method for QAOA angle finding. In this work, we systematically study QAOA parameter transferability from small problem sizes (16 and 27 decision variables) onto large problem instances (up to 156 qubits) for heavy-hex graph Ising models with geometrically local higher-order terms using the Julia based QAOA simulation tool JuliQAOA to perform classical angle finding for up to 49 QAOA layers $\left(p\right)$. Parameter transfer of the fixed angles is validated using a combination of full state vector, projected entangled pair states, matrix product state, and LOWESA numerical simulations. We find that the QAOA parameter transfer from single instances applied to other (unseen) problem instances does not in general provide monotonically improving performance as a function of $p$—there are many cases where the performance temporarily decreases as a function of $p$—but despite this the transferred angles have a general trend of improved expectation value as the QAOA depth increases, in many cases converging close to the true ground-state energy of the $100+$ qubit instances. We also sample the hardware-compatible Ising models using the ensemble of transfer-learned QAOA parameters on several superconducting qubit IBM quantum processors with 127, 133, and 156 qubits. We find continuous solution quality improvement of the hardware-compatible QAOA circuits run on the IBM noisy intermediate-scale quantum processors up to $p=5$ on ibm_fez, up to $p=9$ on ibm_torino, and up to $p=10$ on ibm_pittsburgh.

When a highly elastic drop of a polymer solution hits a superhydrophobic surface at a high speed, a growing tail-like filament emerges vertically from the impact spot as the contact line recedes. Notably, the ligament transitions into a balloonlike shape before detaching completely from the surface (balloon regime). The ligament formation is attributed to liquid impalement upon impact into the surface protrusion spacing, and elastic forces due to polymers prevent ligament breakup. The detachment of the ligament happens when polymeric stresses balance or overcome the adhesion at the surface. This study shows that tuning droplet rheology and surface roughness enables droplets to rebound completely and without splashing at high impact speeds.

Soft hydrogels are widely used as antifouling coatings because they strongly suppress deposition of particles, cells, and microorganisms from flowing aqueous suspensions, yet the physical origin of this resistance remains unclear, as several near-wall phenomena occur simultaneously over rapidly changing length scales. Here, we combine deposition kinetics, single-particle trajectory tracking, and independent measurements of adhesion dynamics to identify the key kinetic barrier. Using polystyrene microbeads depositing onto a submicron poly(ethylene glycol) hydrogel coating in a parallel-plate flow cell, we examine how the near-wall deceleration of depositing particles during the last few seconds preceding arrest compares with the one expected for particles rolling in contact with the surface and decelerating through adhesive force maturing over time. Estimating the latter using a braking model, derived from the adhesion dynamics extracted from AFM force spectroscopy using identical colloidal probes and surface, predicts immobilization of several orders of magnitude faster than observed. When further combined with attachment rate constants deduced from the variation of the deposition rate along the channel and their ionic-strength dependence, this disagreement rules out rolling-in-contact scenario. This implies that most particles stay hovering above the surface, separated from the hydrogel by a thin fluid gap maintained by a repulsive force. We further rule out as such force both the electric double-layer interactions, attractive in the present system, and the inertial lift, as it is negligible at the present shear rates. This points to elastohydrodynamic lift (EHL)—arising from pressure-deformation coupling in lubrication flow amplified by large compliance of the hydrogel—as the only plausible barrier force. Using mechanical parameters measured by AFM and established EHL scaling, we show that EHL can indeed impose a sufficient kinetic barrier at a few tens of nanometers from the surface, cutting off attractive adhesion forces and suppressing deposition.

Quantum heat engines are nanoscale devices that convert heat into work by exploiting quantum effects, such as coherence and interference. Previous studies of these devices did not consider spin-dependent effects, which can influence the thermoelectric performance of the engine. In this work, we study the thermoelectric behavior of a quantum heat engine based on an Aharonov-Bohm ring—a mesoscopic ring where electrons exhibit interference depending on the magnetic flux it encloses—incorporating Rashba spin-orbit interaction (SOI), which couples the electron's motion and spin. We find that Rashba SOI enhances the figure of merit $ZT$, a measure of the engine's conversion efficiency. Our results suggest that controlling spin-dependent interference could lead to improvements in the fabrication of efficient thermoelectric devices.

Active nematics have served as model systems for studying defect dynamics for decades, yet the general mechanism of defect formation in three dimensions (3D) remains unclear. Here, we introduce the principal-plane framework to study disclination-loop nucleation in 3D active nematics. This approach intuitively captures the 3D director field around disclinations and connects perturbative instability analysis with geometric characterization. With particle-based simulations, we further reveal that disclinations arise from the bend instability, while their tilt reflects the competition between activity and elasticity. We show that an activity-dependent effective stiffness ${\kappa }_{\text{eff}}=\kappa /(1+2f_{\text{a}}^2)$ governs both defect morphology and the system's steady behavior. Together, these results establish a unified picture of disclination-loop emergence and provide design principles for controlling defect-driven dynamics in orientational materials.

The prediction of quantum dynamical responses lies at the heart of modern physics. Yet, modeling these time-dependent behaviors remains a formidable challenge because quantum systems evolve in high-dimensional Hilbert spaces, often rendering traditional numerical methods computationally prohibitive. While large language models have achieved remarkable success in sequential prediction, quantum dynamics presents a fundamentally different challenge: forecasting the entire temporal evolution of quantum systems rather than merely the next element in a sequence. Existing neural architectures such as recurrent and convolutional networks often require vast training datasets and suffer from spurious oscillations that compromise physical interpretability. In this work, we introduce an approach: Kolmogorov-Arnold networks (KANs) augmented with physics-informed loss functions that enforce the Ehrenfest theorems. Our method achieves superior accuracy with significantly less training data: It requires only $5.4\%$ of the samples (200) compared to temporal convolution networks (3700). We further introduce the chain of KANs, an architecture that embeds temporal causality directly into the model design, making it particularly well suited for time series modeling. Our results demonstrate that physics-informed KANs offer a compelling advantage over conventional black-box models, maintaining both mathematical rigor and physical consistency while dramatically reducing data requirements.

We present the ultrafast dynamics of the interaction between a high-intensity extreme contrast (expected to be around $\sim {10}^{-18}$ at hundreds of picoseconds timescale) femtosecond laser and a solid. Simultaneous measurements of probe Doppler spectrometry and reflectivity in pump-probe experiments reveal the presence of extreme pressure in the solid density region, which triggers a long-lived ($\sim 15$ ps) strong inward shock. Hydrodynamic simulations accurately replicate these observations, providing a detailed explanation of the underlying physics.

High-energy ion irradiation deposits extreme energy in a narrow range (∼1–10 nm) along ion trajectories in solid through electronic energy loss, producing unique irradiation effects such as ion tracks. However, intrinsic velocity effects impose an upper limit on electronic energy loss that cannot be overcome by adjusting irradiation parameters. We introduce a method using electric fields during irradiation to enhance nanoscale energy deposition by accelerating ion-excited electrons within subpicosecond timescales. Our extended field-enhanced thermal spike model quantitatively describes this enhancement and predicts a significant reduction in the electronic energy loss required for ion track formation in amorphous ${\mathrm{SiO}}_2$, which is in excellent agreement with experimental observations. This work provides an approach to control energy deposition during irradiation and boosts the wide application of ion tracks in material modification and nanoengineering to much broader extents.

Equilibrium molecular dynamical simulations are performed to investigate the isomorphic properties of the supercritical liquidlike to gaslike transition in Yukawa fluids. From the calculated Pearson correlation coefficient $R$, the isomorph theory is always applicable in both the liquidlike and gaslike states of Yukawa systems, so that the Frenkel line is also an isomorphic curve, as discussed here. Based on the isomorph theory, it is proposed that the height of the first peak of the radial distribution function $g\left(r_{\mathrm{fp}}\right)$ can be used as a convenient and sensitive criterion of the Frenkel line, which is $g\left(r_{\mathrm{fp}}\right)=1.2$ for two-dimensional and $g\left(r_{\mathrm{fp}}\right)=1.14$ for three-dimensional Yukawa fluids. This criterion of the Frenkel line from $g\left(r_{\mathrm{fp}}\right)$ well agrees with the widely accepted condition of $C_{\mathrm{T}}/v_{\mathrm{th}}=\sqrt{2}$ for the supercritical transition, as well as the equivalent of the reduced instantaneous shear modulus $G_{\infty }/n{k}_{\mathrm{B}}T=2$. The criterion of $g\left(r_{\mathrm{fp}}\right)$ provides a convenient method to identify the supercritical transition of dusty plasmas or Yukawa fluids, which may be extended to other physical systems.

The scaling behavior of fully flexible elastic tethered surfaces has been debated for decades. Some theories predict that self-avoiding surfaces would crumple in the absence of bending rigidity, while most simulations suggested that they would remain flat. Recent simulations on ideal membranes with lattice perforations suggest that systematically removing surface area from a membrane may provide an alternative way to crumpling self-avoiding surfaces. We perform extensive numerical simulations of two models of fully flexible elastic tethered surfaces in which self-avoidance can be systematically and continuously tuned to the ideal limit. We show that in the thermodynamic limit, these surfaces remain flat with a size exponent $\nu =1$ for any finite degree of self-avoidance, with or without membrane perforations.

We propose a scalable qudit-based quantum processor using rotational states of polar molecules. Previously, molecular internal states were used to enlarge Hilbert space, whereas our approach uses optical tweezer arrays to achieve scalable architectures with exponential state-space growth without increasing qudit dimensionality $d$. Entangling gates are implemented by adiabatically bringing traps together to activate dipole-dipole interactions. We develop encoding schemes mapping single qubits into qudits with $2\le d\le 5$ and pairs of qubits into $d=4,5$ qudits, enabling universal set of quantum gates. Additional levels in $d=3$ and $d=5$ qudits simplify multiqubit gate decompositions. We analyze experimental parameters for SrF and NaCs molecules. This approach provides a promising route to scalable quantum information processing with multilevel systems using existing experimental platforms.

Input-output theory is a well-known tool in quantum optics and ubiquitous in the description of quantum systems probed by light. Owing to the generality of the setup it describes, the theory finds application in a wide variety of experiments in circuit and cavity QED. We present an approach to input-output theory using the Schwinger-Keldysh path integral formalism that gives us direct access to the full output field statistics such as the first- and second-order coherence functions. By making the rich toolbox of nonequilibrium quantum field theory accessible, our formalism greatly simplifies the treatment of nonlinear systems and provides a uniform way of obtaining perturbative results. We showcase this particular strength by computing the output field statistics of a Kerr nonlinear oscillator at finite temperatures through the use of diagrams and diagram summation techniques. We find a reduction in reflection that is not due to photon leakage but rather associated to the squeezing of the output light.

We show that globally coupled phase oscillators inherently possess a phase frustration when four-body interactions are considered. This intrinsic frustration arises when oscillators have asymmetric distributions of initial conditions spanning across multiple fixed points. Moreover, when the frequency distribution is bimodal, the two groups of oscillators may evolve toward distinct macroscopic dynamical behaviors, with one group being synchronized and the other remaining asynchronous. This constitutes a mechanism for the emergence of chimera states, and one that is specifically characteristic of higher-order interactions.

This work demonstrates high-repetition-rate laser-driven ion acceleration utilizing optically shaped gaseous targets. The optical shaping is achieved via dual, intersecting, counterpropagating laser-generated blast waves that precisely shape the underdense gas into long-lived, controlled, and reproducible near-critical density targets. The compressed target persists for several nanoseconds, time long enough to allow for the excellent synchronization between the target and the main accelerating femtosecond laser beam. Measurements of multi-MeV ion energy spectra are presented. Three-dimensional (3D) hydrodynamic simulations are used to optimize the density profile and assess the influence of the amplified spontaneous emission of the femtosecond accelerating laser pulse. A synthetic optical probing model is applied to directly compare simulations with experimental data. 3D particle-in-cell simulations reveal the formation of multi-kT, azimuthal magnetic fields, strongly suggesting magnetic vortex acceleration as the main acceleration mechanism.

We investigated electron-nuclear spin entanglement in the paramagnetic ground state of the Ho-based cubic compound ${\mathrm{HoCo}}_2{\mathrm{Zn}}_{20}$. From analyses of magnetization and specific heat data, we determined the cubic crystalline electric field (CEF) parameters, the magnetic exchange constant, and the hyperfine coupling constant between the $4f$ magnetic moment and the ${}^{165}\mathrm{Ho}$ nuclear spin. Our results show that the ${\mathrm{\Gamma }}_5$ CEF ground state is split by the hyperfine coupling, with an energy width of 1.3 K at 0 T, and that the true paramagnetic ground state is a quasisextet arising primarily from entanglement between the $f$-electron effective spin $S=1$ and the ${}^{165}\mathrm{Ho}$ nuclear spin $I=7/2$. We further demonstrate that, depending on the CEF parameters, the paramagnetic ground state can switch to an electron-nuclear coupled dectet. These findings underscore the importance of accurately identifying the electron-nuclear level scheme for understanding the low-temperature properties of rare-earth compounds containing spin-active nuclei.

${\mathrm{UCd}}_{11}$ is an antiferromagnetic uranium intermetallic compound ($T_{\mathrm{N}}=5.3\mathrm{K}$) with enhanced electron mass and uranium-uranium spacings nearly twice the Hill limit, suggesting a weakly hybridized $5f$ electronic character. Various x-ray spectroscopy techniques indicate that uranium in ${\mathrm{UCd}}_{11}$ adopts the formal ${\mathrm{U}}^{3+}5f^3$ configuration, while core-level photoemission spectroscopy (PES) data of ${\mathrm{UCd}}_{11}$ reveal only a weak satellite feature, typically interpreted as a signature of itinerancy. In this work, we present density functional theory (DFT) combined with dynamical mean-field theory (DMFT) calculations of ${\mathrm{UCd}}_{11}$, using material-specific parameters tuned to reproduce valence-band PES spectra at different photon energies, thereby exploiting the energy dependence of photoionization cross sections. Our results demonstrate that ${\mathrm{UCd}}_{11}$ is a highly localized uranium $5f^3$ system. Furthermore, core-level spectra obtained from a $\mathrm{DFT}+\mathrm{DMFT}$ Anderson impurity model reveal that, contrary to common assumptions, the presence or absence of satellite structures is not a reliable indicator of strong correlations or itinerant $5f$ behavior.

Decoherence in quantum devices, such as qubits and resonators, is often caused by bistable fluctuators modeled as random telegraph noise (RTN), leading to significant dephasing. We analyze the impact of individual and multiple fluctuators on a bosonic mode in continuous variable systems, identifying non-Markovian behavior governed by two timescales: the switching rate ($\xi$) and the coupling strength ($\nu$) of the fluctuator. Using the Breuer-Laine-Piilo trace-distance measure, we characterize non-Markovianity for both Gaussian and non-Gaussian states, revealing that for rotation-symmetric bosonic (RSB) codes, known for their error-correction advantages, the measure grows linearly with code symmetry and can become unbounded. We evaluate the performance of these RSB codes under simultaneous loss and RTN dephasing. For a teleportation-based Knill error-correction circuit, the codes perform robustly in the Markovian limit. In the non-Markovian regime, the performance depends nontrivially on the time at which the error correction is performed. The average gate fidelity of the error-corrected state in this case exhibits oscillations as a function of time due to the oscillatory nature of the dephasing function of the RTN noise; however, for most of the parameter ranges, the values stay beyond the breakeven point. Extending to multiple fluctuators that produce $1/f$ noise, we observe that non-Markovianity decays with increasing fluctuator count, while the performance of RSB codes remains effective with increasing number of fluctuators.