We propose an innovative design for an optical echo state network (ESN), an advanced type of reservoir computer known for its universal computational capabilities. Our design enables an optical implementation of arbitrary ESNs, featuring flexibility in optical matrix multiplication and nonlinear activation. Leveraging the nonlinear characteristics of stimulated Brillouin scattering, the architecture efficiently realizes measurement-free nonlinear activation. The approach significantly reduces computational overhead and energy consumption compared to traditional software-based methods. Comprehensive simulations validate the system's memory capacity, nonlinear processing strength, and polynomial algebra capabilities, showcasing performance comparable to software ESNs across key benchmark tasks. Our design establishes a feasible, scalable, and universally applicable framework for optical reservoir computing, suitable for diverse machine learning applications.

Identifying nonlinear dynamical systems characterized by nonlinear parameters presents significant challenges in deriving mathematical models that enhance understanding of physical phenomena. Traditional methods, such as Sparse Identification of Nonlinear Dynamics (SINDy) and symbolic regression, can extract governing equations from observational data; however, they also come with distinct advantages and disadvantages. This paper introduces a differentiable optimization methodology within the SINDy framework, termed ADAM-SINDy, which synthesizes the strengths of established approaches by employing the ADAM optimization algorithm. This integration facilitates the simultaneous optimization of nonlinear parameters and coefficients associated with nonlinear candidate functions, enabling efficient and precise parameter estimation without requiring prior knowledge of nonlinear characteristics such as trigonometric frequencies, exponential bandwidths, or polynomial exponents, thereby addressing a key limitation of the classical SINDy framework. Through an integrated global differentiable optimization, ADAM-SINDy dynamically computes all unknown variables in response to system-specific data, resulting in a more adaptive and efficient identification procedure that reduces the sensitivity to the library of candidate functions. The performance of the ADAM-SINDy methodology is demonstrated across a spectrum of dynamical systems, including benchmark coupled nonlinear ordinary differential equations such as oscillators, chaotic fluid flows, reaction kinetics, pharmacokinetics, as well as nonlinear partial differential equations (wildfire transport). The results demonstrate significant improvements in identifying parameterized dynamical systems and underscore the importance of concurrently optimizing all parameters, particularly those characterized by nonlinear parameters. These findings highlight the potential of ADAM-SINDy to extend the applicability of the SINDy framework in addressing more complex challenges in dynamical system identification.

Time-delayed effects are widely present in nature, often accompanied by distinctive nonequilibrium features, such as net heat flow from a single thermal bath to the system. To elucidate detailed structures of the dissipation, we study the frequency decomposition of the heat dissipation in linear time-delayed Langevin systems. We decompose the heat dissipation into frequency spectrum using the Harada-Sasa equality, which relates the heat dissipation to the violation of the fluctuation response relation (FRR). We find a characteristic oscillatory behavior in the spectrum, and the oscillation asymptotically decays with an envelope inversely proportional to the frequency in the high-frequency region. Furthermore, the oscillation over the low-frequency region reflects the magnitude and sign of the heat dissipation. We confirm the generality of the results by extending our analysis to systems with multiple delay times. Since the violation of FRR is experimentally accessible, our results suggest an experimental direction for detecting and analyzing detailed characteristics of dissipation in time-delayed systems.

We challenge two foundational principles of localization physics by analyzing conductance fluctuations in two dimensions with unprecedented precision: (1) the Thouless criterion, which defines localization as insensitivity to boundary conditions, and (2) that symmetry determines the universality class of Anderson localization. We reveal that the fluctuations of the conductance logarithm fall into distinct subuniversality classes inherited from Kardar-Parisi-Zhang (KPZ) physics, dictated by the lead configurations of the scattering system and unaffected by the presence of a magnetic field. Distinguishing between these probability distributions poses a significant challenge due to their striking similarity, requiring sampling beyond the usual threshold of $\sim {10}^{-6}$ accessible through independent disorder realizations. To overcome this, we implement an importance sampling scheme—a Monte Carlo approach in disorder space—that enables us to probe rare disorder configurations and sample probability distribution tails down to ${10}^{-30}$. This unprecedented precision allows us to unambiguously differentiate between KPZ subuniversality classes of conductance fluctuations for different lead configurations, while demonstrating the insensitivity to magnetic fields.

Recently, a surrogate model was proposed that employs a factorization machine to approximate the underlying input-output mapping of the original system, with quantum annealing used to optimize the resulting surrogate function. Inspired by this approach, we propose an enhanced surrogate model that incorporates additional slack variables into both the factorization machine and its associated Ising representation, thereby unifying what was by design a two-step process into a single, integrated step. During the training phase, the slack variables are iteratively updated, enabling the model to account for higher-order feature interactions. We apply the proposed method to the task of predicting drug combination effects. Experimental results indicate that the introduction of slack variables leads to a notable improvement of performance. Our algorithm offers a promising approach for building efficient surrogate models that exploit potential quantum advantages.

Understanding the structural organization of bipartite networks is essential for characterizing the architecture and dynamics of complex systems, from ecological communities to technological and social interactions. Such networks often exhibit recurring patterns—nestedness, modularity, in-block nestedness—that shape system stability, diversity, and function. Yet, despite extensive research, assessing the statistical significance of these patterns remains problematic, as existing null models may introduce systematic biases that can lead to contradictory interpretations. Here, we develop a generative framework that analytically constructs synthetic bipartite networks spanning the most common structural regimes and use it to perform a comprehensive evaluation of state-of-the-art null models. Across large synthetic and empirical ensembles, we show how commonly used null models inconsistently estimate the significance of nested, modular, and compound architectures, depending on how degree constraints are imposed. Building on these insights, we introduce a corrected probabilistic model that reconciles, to some extent, these inconsistencies, providing a more balanced basis for significance testing. Our work thus establishes a unified theoretical and computational framework for generating, analyzing, and interpreting structure in bipartite networks, offering conceptual and methodological guidance for future research in ecology and beyond.

We theoretically show that the quantum efficiency (QE) of photoemission can be dramatically enhanced by reducing the laser pulse duration to a few optical cycles. Using an exact quantum theory for ultrafast photoemission, we find that QE can increase by several orders of magnitude as the pulse length decreases from tens of cycles to a few cycles, at fixed low laser intensities. The corresponding photon order of the multiphoton process is also significantly reduced, indicating a shift in the underlying emission mechanism. We find that the carrier-envelope phase strongly modulates the photoelectron spectrum and QE in the few-cycle regime; however, counterintuitively, its influence diminishes for subcycle pulses. The results open up opportunities for enhancing and controlling ultrafast electron emission through optical pulse shaping in the low-intensity regime, with potential applications in attosecond science, ultrafast electron sources, and light-wave-driven quantum devices. The macroscopic enhancement of photoemission efficiency driven by few-cycle optical fields may be considered as yet another example of macroscopic quantum phenomena.

Parity-time $\left(PT\right)$-symmetric Hamiltonians exhibit nonunitary dynamical evolution while maintaining real spectra, and offer unique approaches to quantum sensing and entanglement generation. Here, we present a method for simulating the quantum dynamics of $PT$-symmetric systems on unitary-gate-based quantum computers by leveraging Hermitian equivalents through similarity transformations. We introduce two algorithms for simulating $PT$-symmetric systems near exceptional points where eigenvalues and eigenstates coalesce. The first is a hybrid classical-quantum algorithm and the second reduces the classical component by using an ancilla qubit. We then use perturbation theory to extend this method to consider the dynamics of two weakly interacting $PT$-symmetric systems. Demonstrations on a quantum device and noisy simulators validate the algorithm on current quantum devices, offering potential for scalable simulations of $PT$-symmetric systems and pseudo-Hermitian operators in quantum computation.

The problem of determining the existence of a spectral gap in a lattice quantum spin system was previously shown to be undecidable for one [Phys. Rev. X 10, 031038 (2020)] or more dimensions [Nature (London) 528, 207 (2015)]. In these works, families of nearest-neighbor interactions are constructed whose spectral gap depends on the outcome of a Turing machine halting problem, therefore making it impossible for an algorithm to predict its existence. While these models are translationally invariant, they are not invariant under the other symmetries of the lattice, a property which is commonly found in physically relevant cases. This poses the question of whether the spectral gap problem could be decidable for Hamiltonians with stronger symmetry constraints. We give a negative answer to this question, in the case of models with four-body (plaquette) interactions on the square lattice satisfying rotation, but not reflection, symmetry: rotational symmetry is not enough to make the problem decidable.

The spin states of the nitrogen vacancy (${\mathrm{NV}}^{-}$) center in diamond are used in, among others, quantum computing, nanoscale imaging, and magnetic field sensing, and have been proposed for fundamental physics experiments. The states of ${\mathrm{NV}}^{-}$ centers are traditionally measured using the spin-state-dependent photoluminescence—a destructive and often inefficient measurement scheme. In this article, using a single laser beam as a pump and a probe, we measure the spin states of the ${\mathrm{NV}}^{-}$ centers nondestructively using the Faraday effect at room temperature. Using the optical selection rules and the helicity-dependent absorption, we identify the optical transitions of the ${\mathrm{NV}}^{-}$ center responsible for the Faraday effect and confirm the existence of spin-orbit coupling in such centers at room temperature. Our results indicate that experiments such as NV spin-photon entanglement and electromagnetically induced transparency are viable in ambient conditions. Finally, using the Faraday effect, we develop a magnetic field sensor and argue that, with the inclusion of an optical cavity, a femtotesla-level magnetic field sensitivity can be achieved.

We study the connection between exceptional points (EPs) and optimal parameter estimation, in a simple system consisting of two counterpropagating traveling wave modes in a microring resonator. The unknown parameter to be estimated is the strength of a perturbing cross-coupling between the two modes. Partially reflecting the output of one mode into the other creates a non-Hermitian Hamiltonian that exhibits a family of EPs, creating an exceptional surface (ES). We use a fully quantum treatment of field inputs and noise sources to obtain a quantitative bound on the estimation error by calculating the quantum Fisher information (QFI) in the output fields, whose inverse gives the Cramér-Rao lower bound on the mean-squared error of any unbiased estimator. We determine the bounds for two input states, namely, a semiclassical coherent state and a highly nonclassical NOON state. We find that the QFI is enhanced in the presence of an EP for both of these input states and that both states can saturate the Cramér-Rao bound. We then identify idealized yet experimentally feasible measurements that achieve the minimum bound for these two input states. We also investigate how the QFI changes for parameter values that do not lie on the ES, finding that these can have a larger QFI, suggesting alternative routes to optimize the parameter estimation for this problem.

We study the rovibronic transitions in ${\mathrm{NaK}}_2$ between its electronic ground state $1^2{A}^{\prime }$ and its second excited state $3^2{A}^{\prime }$, to identify possible pathways for the creation of ultracold ground-state triatomic molecules. Our methodology relies on the computation of potential energy surfaces and transition dipole moment surfaces for the relevant electronic states using ab initio methods. Rovibrational energy levels and wave functions are determined using the discrete variable representation approach. A double-well structure of the potential energy surface is identified for both states, and the related transition strengths between the rovibrational levels are derived. Our calculations show that the formation of ultracold ground-state ${\mathrm{NaK}}_2$ molecules is expected when starting from an excited electronic state of ${\mathrm{NaK}}_2$, which can be created by photoassociation of NaK and K, as observed by optical means by Cao, et al. [Phys. Rev. Lett. 132, 093403 (2024)].

Precise spectral control in the hard x-ray regime remains a long-standing challenge that limits applications in atomic-scale science and ultrafast spectroscopy. We present a proposal and numerical study of an actively mode-locked cavity-based x-ray free-electron laser that achieves deterministic spectral programmability with phase-locked pulse trains and comblike spectra, by coherently modulating the electron-beam energy. Three-dimensional time-dependent simulations predict $700\mu \mathrm{J}$ total energy, $30\mathrm{G}\mathrm{W}$ peak power, and frequency-comb spacing of $1.55\mathrm{e}\mathrm{V}$ set by the modulation frequency. We further develop selective single-line amplification via undulator tapering and absolute frequency positioning through modulation-laser tuning with meV precision. Importantly, stable mode-locked operation persists under >80% peak-to-peak cavity-reflectivity variations, substantially relaxing requirements on x-ray optics. These results establish active mode locking as a practical route to fully coherent, spectrally agile hard x-ray sources and enable opportunities in time-resolved core-level spectroscopy, x-ray quantum optics, and precision metrology.

We present a theory of geodynamics in a spacetime crystal based on an event wave packet constructed from the Floquet-Bloch waves, which involves not only a scalar dispersion function but also a Berry curvature tensor in the phase space manifold of spacetime and the reciprocal quasi-energy-momentum. In the presence of structural deformation, this theory is naturally extended into a covariant form with the introduction of a lattice connection constructed out of the gradients of the local lattice vectors. This geometric framework reveals three distinct gravitational forces: lattice deformation gravity, dispersion gravity, and Berry curvature gravity. These forces manifest as distinct, experimentally tunable connection and metric terms in the geodynamics, establishing a framework for engineering artificial spacetime by controlling lattice strain, band structure, and wave function topology. Our work provides a direct conceptual link between general relativity and condensed matter physics, opening a path toward the laboratory realization of novel gravitational phenomena.

We present a cardinal solution for the long-standing and fundamental problem associated with the adiabatic, reversible, and controlled excitation of both dark and bright solitons in Kerr microresonators with normal group-velocity dispersion. Our findings stem from the inclusion of a localized non-Hermitian potential, which we use to drastically reshape the characteristic collapsed snaking structure associated with such solitons. Consequently, we demonstrate a snaking-free bifurcation landscape where solitons of all possible widths are continuously connected via the dynamic change of the cavity detuning, and hence dissipative localized states of unprecedentedly high pump-to-comb conversion efficiencies can be excited in an adiabatic, deterministic, and reversible fashion. Our fundamental discovery has practical implications of paramount importance for frequency comb generation in all-normal dispersion cavities, which are key to comb generation in most spectral regions away from the telecom bands.

Ultraintense and ultrashort x-ray free-electron laser (XFEL) pulses promise single particle imaging (SPI) via enabling collection of diffraction data for nanocrystals, or nano-size nonperiodic objects before the destruction of the sample. Photoionization and subsequent processes lead to plasma generation within the sample in such experiments. The continuum energy levels of electrons for atoms and atomic ions are lowered due to plasma screening, also known as ionization potential depression (IPD). We theoretically investigate the plasma formation and the effect of IPD in the context of SPI with calculations performed on bulk glycine, mimicking the interior of irradiated biological macromolecules, e.g., proteins or viruses. To simulate the plasma formation dynamics, we employ a nonequilibrium, hybrid quantum-classical approach, combined with the evaluation of the transient IPD from first-principles electronic structure calculations considering the time-dependent microscopic environment, which in earlier work was applied to a solid-density plasma consisting of a single atomic species [Phys. Rev. E 106, 015206 (2022)]. Here, this approach is extended to more than one atomic species for applications to biological macromolecules in SPI studies. Our work quantifies the effect and importance of IPD in XFEL-based imaging of biological systems and provides further guidance for simulations of electronic radiation damage dynamics toward successful SPI experiments.