Although one-dimensional classical spin chains do not exhibit phase transitions, we found that a phase transition does occur when they are coupled to a cavity photon mode. This provides the simplest exactly solvable examples demonstrating that finite-temperature superradiant phase transitions can emerge from long-range fully connected interactions mediated by photons and interactions within the material.

Optical refrigeration of solids with anti-Stokes fluorescence has been widely explored as a vibration-free cryogenic cooling technology. A minimum temperature of 87 K has been demonstrated with rare-earth-ion-doped crystals using optical refrigeration. However, the depletion of the upper-lying energy levels in the ground-state manifold hinders further cooling to below the liquid nitrogen $\left({\mathrm{LN}}_2\right)$ temperatures, restricting its applications. In this work, we introduce a Purcell-enhanced optical refrigeration method to circumvent this limitation. This approach enhances the emission of high-energy photons by coupling the emitters to an optical cavity, blueshifting the mean emission wavelength. Such Purcell-enhanced emission facilitates cooling starting from a lower-energy level in the ground-state manifold, which exhibits a higher occupation below the ${\mathrm{LN}}_2$ temperatures. Using experimentally measured optical coefficients, our theoretical analysis predicts a minimum achievable internal temperature of about 38 K for a ${\mathrm{Yb}}^{3+}:{\mathrm{YLiF}}_4$ nanocrystal near a cavity under realistic conditions. The proposed method is applicable to other rare-earth-ion-doped materials and semiconductors and will have applications in creating superconducting and other quantum devices through solid-state cooling.

We investigate quantum reservoir computing (QRC) using a hybrid qubit-boson system described by the Jaynes-Cummings (JC) Hamiltonian and its dispersive limit (DJC). These models provide high-dimensional Hilbert spaces and intrinsic nonlinear dynamics, making them powerful substrates for temporal information processing. We systematically benchmark both reservoirs through linear and nonlinear memory tasks, demonstrating that they exhibit an unusual superior nonlinear over linear memory capacity. We further test their predictive performance on the Mackey-Glass time series, a widely used benchmark for chaotic dynamics, and show comparable forecasting ability. We also investigate how memory and prediction accuracy vary with reservoir parameters and show the role of higher-order bosonic observables and time multiplexing in enhancing expressivity, even in minimal spin-boson configurations. Our results establish JC- and DJC-based reservoirs as versatile platforms for time-series processing and as elementary units that overcome the setting of equivalent qubit pairs and offer pathways toward tunable, high-performance quantum machine learning architectures.

We develop a general framework for classifying fermionic dynamical systems with measurements using symmetry and topology. We introduce two complementary classification schemes based on the Altland-Zirnbauer tenfold way: (1) the many-body evolution operator (mEO) symmetry class, which classifies fermionic dynamics at the many-body level and naturally extends to interacting dynamics, and (2) the single-particle transfer matrix symmetry class, which classifies free-fermion dynamics at the single-particle level and connects to Anderson localization physics. In the free-fermion limit, we show that these two frameworks are equivalent via a dynamical bulk-boundary correspondence: The topology of the dynamical system's spacetime bulk determines the topology of the area-law-entangled steady-state ensemble living on its temporal boundary. Next, we prove that symmetry-invariant, postselection-free Gaussian measurements are realizable in only four of the ten mEO classes (A, AI, BDI, D); the remaining six require either postselection or interacting (non-Gaussian) measurements. Building on these results, we construct general postselection-free topological adaptive circuits that realize topological dynamical phases in any spatial dimension for the four admissible mEO classes. These circuits simultaneously provide a protocol for preparing and stabilizing free-fermion topological states in all ten symmetry classes. As a concrete demonstration, we construct and simulate $2+1\mathrm{d}$ adaptive circuits that realize mEO-class-A topological dynamics, steering toward a steady-state ensemble of Chern insulators in $\mathcal{O}\left(1\right)$ circuit depth. Finally, we numerically characterize topological phase transitions, dynamical domain-wall modes, and robustness to coherent noise, identifying finite error thresholds at which trajectory-resolved and trajectory-averaged quantities undergo distinct phase transitions.

We have extended the two-color bicircular approach for generating chiral XUV radiation via high-harmonic generation by combining femtosecond driving laser fields with 1:3 frequency ratio of wavelengths 1200 and 400 nm. With optimized driving-field intensities, we produced highly chiral spectra in which the vast majority of harmonics sharing the same helicity constitute the vast majority of spectral content. We support these experimental finding with a numerically comprehensive analytical model that describes the propensity (selection) rules for emission of circularly polarized high harmonics. We identify and confirm the rules responsible for the contrast between the allowed odd harmonics of orders $4q+1$ and $4q-1$ ($q$ an integer), which posses opposite helicities, as well as the complete prohibition of even-order harmonics in the high-harmonic spectra. We further apply these rules to explain the spectral shape and ellipticity of the emitted odd harmonics as functions of both the intensity and the ellipticity of the driving-field components. Using XUV polarimetry, we retrieved full Stokes vector, confirming achieved ellipticities higher than 0.9.

The nature of the melting transition in two-dimensional systems of particles has attracted considerable research attention since the development of Kosterlitz-Thouless-Halperin-Nelson-Young theory. The hexatic phase proposed by this theory has been recently identified experimentally in ensembles of magnetic skyrmions, quasiparticles formed in a magnetically ordered crystal. Here, we use quasiparticle dynamical simulations to study how the anisotropy of the skyrmion-skyrmion interactions induced by the atomic lattice influences the melting transition. For isotropic interactions, we find a transition from a solid phase through a hexatic phase stable in a narrow temperature range to an isotropic liquid phase. However, if the interactions between skyrmions are forced to be anisotropic by the atomic lattice, then a direct solid-liquid transition can be observed with orientational order persisting up to temperatures of 30 K in the liquid phase.

We use a transmon qubit and its dispersively coupled readout resonator to measure the Fock state populations of another microwave resonator, to which we have attached a quantum-circuit refrigerator (QCR). First, we apply noise generated at room temperature to the resonator and show that such noise drive leads to a thermal distribution of the resonator Fock states. Subsequently, we detune the noise frequency band far away from the resonance condition and vary the power of the noise applied on the QCR. We observe that such artificial thermal noise may lead to major damping of a coherent state of the resonator. Importantly, we also demonstrate that the effective temperature of a thermal resonator state can be reduced from roughly 300 to 130 mK by the introduction of the artificial thermal noise. These observations pave the way for a purely thermally powered quantum-circuit refrigerator that may unlock the use of waste heat in resetting superconducting qubits in a quantum processor and in building autonomous quantum heat engines.

We numerically investigate the phase behavior of thick shells of cholesteric liquid crystals with tangential anchoring at the shell boundary. For achiral liquid crystals, we demonstrate a thickness-dependent transition from a configuration featuring four disclination lines connecting the inner and outer surfaces to a defect-free bulk state, where each surface is topologically isolated and features two boojums. Incorporating chirality stabilizes defect arrangements, including a mixed state combining boojums and disclination lines, as well as blue phases at high chirality, and we show that shell thickness strongly modulates these transitions. We exploit the metastable features of the observed phases to obtain an elastically induced rearrangement of the shell surfaces during a cholesteric hysteresis cycle, stabilizing an alternative configuration that minimizes the free energy at low chirality. Finally, we consider the case of shells featuring multiple inner isotropic cores, that induce a topological and morphological reorganization, where some inclusions form a connected cluster with the outer shell, while the remaining inclusions become isolated. Our work paves the way for exploring dynamic behaviors under external fields, mixed anchoring conditions, or active flows.

We present the combination of a complex-time tensor-network impurity solver with an analytic continuation scheme based on exponential fitting as an efficient framework for single and multiorbital dynamical mean-field calculations. By performing time evolution along a complex-time contour, the approach balances computational cost with the difficulty of spectral recovery, offering greater flexibility than methods confined to the real or imaginary axis. By complementing the complex-time evolution with an exponential fitting scheme, we faithfully extract real-time information at negligible cost. The resulting method obtains high-resolution spectra at a significantly lower computational cost than real-time evolution, offering a promising tool for ab initio studies of strongly correlated materials.

Quantum process learning is emerging as an important tool to study quantum systems. While studied extensively in coherent frameworks, where the target and model system can share quantum information, less attention has been paid to whether the dynamics of quantum systems can be learned without the system and target directly interacting. Such incoherent frameworks are practically appealing since they open up methods of transpiling quantum processes between the different physical platforms without the need for technically challenging hybrid-entanglement schemes. Here, we provide bounds on the sample complexity of learning unitary processes incoherently by analyzing the number of measurements that are required to emulate well-established coherent learning strategies. We prove that if arbitrary measurements are allowed, then any efficiently representable unitary can be efficiently learned within the incoherent framework; however, when restricted to shallow-depth measurements, logarithmic depth unitaries can be learned but there exist linear-depth unitaries that are unlearnable. We demonstrate our incoherent learning algorithm for low-entangling unitaries by successfully learning a 16-qubit unitary on ibmq_kolkata, and further demonstrate the scalability of our proposed algorithm through extensive numerical experiments.

Understanding interactions between excitons and correlated electronic states presents a fundamental challenge in quantum many-body physics. Here, we introduce a purely electronic model for the formation of exciton polarons in moiré lattices. Unlike conventional approaches that treat excitons as tightly bound bosonic particles, our model considers only electronic degrees of freedom, describing excitons as electron-hole bound states. Our findings reveal a pronounced renormalization of the polaron mass as a function of electron density, particularly near correlated insulators, consistent with recent transport experiments. Additionally, we predict an observable sign change in the effective polaron mass when increasing the electron density that can be measured in Hall-type experiments. Our purely electronic model provides a unified framework to investigate the formation and renormalization of exciton polarons in correlated states.

Simulation of mesoscopic nanostructures is a central challenge in condensed matter physics and device applications. First-principles methods provide accurate electronic structures but are computationally too demanding to simulate mesoscopic nanostructures. Though empirical band theories are efficient for the simulation of nanostructures, their validities are limited by the empirical parametrization that usually lacks the consideration of microscopic wavefunctions and do not hold the transferability. In this work, we propose a methodology that bridges these approaches, achieving first-principles-level reliability with computational efficiency through a tight-binding framework. Our approach starts with Wannier tight-binding (WTB) parameters from small nanostructures, which serve as training data for fitting. To remove the gauge freedom of Wannier functions that obscures size- and geometry-dependent parameter trends, we construct gauge-independent (GI) bases and transform the WTB model into a gauge-independent WTB (GI-WTB) model. This enables robust parameter fitting and prediction of parameter variations, yielding the parametrized GI-WTB (P-GI-WTB) model. Applied to ${\mathrm{MoS}}_2$ armchair-edge nanoribbons, the P-GI-WTB model shows excellent agreement with first-principles results and enables reliable simulations of sub-$\mu \mathrm{m}$-wide nanoribbons. This framework offers a scalable approach for predicting the electronic properties of realistic nanostructures at a computational cost far lower than that of conventional first-principles methods.

We report on a measurement of the energy resolution that can be attained in liquid xenon when recording only the scintillation light. Our setup is optimized to maximize light collection and uses state-of-the-art, high-PDE (photodetection efficiency), VUV-sensitive silicon photomultipliers. We find a value of $3.7\%\pm 0.4\%$ at 511 keV, once saturation effects are corrected for, a result close to the Poissonian resolution that we expect in our setup ($2.8\%\pm 0.4\%$ at 511 keV). Our results in the intrinsic resolution ($2.3\%\pm 0.8\%$) are compatible, within errors, at 511 keV, with those found by theoretical estimations that have been standing for the last 20 years, $1.8\%$. Our work opens possibilities for apparatus based on liquid xenon and using scintillation only. In particular, it suggests that modular scintillation detectors using liquid xenon can be very competitive as building blocks in segmented calorimeters, with applications to Positron Emission Tomography technology.

The quantum period-finding (QPF) algorithm can compute the period of a function exponentially faster than the best-known classical algorithm. In standard QPF, the output state has a primary contribution from $r$ high-probability bit strings, where $r$ is the period. Measurement of this state, combined with continued fraction analysis, reveals the unknown period. Here, we explore a different approach to QPF, where the period is obtained from single-qubit quantities—specifically, the set of one-qubit reduced density matrices (1-RDMs)—rather than the output bit strings of the entire quantum circuit. Using state-vector simulations, we compute the 1-RDMs of the QPF circuit for a generic periodic function. Analysis of these 1-RDMs as a function of period reveals distinctive patterns, which allows us to obtain the unknown period from the 1-RDMs using a numerical root-finding approach. Our results show that the 1-RDMs—a set of $\mathcal{O}\left(n\right)$ one-qubit marginals—contain enough information to reconstruct the period, which is typically obtained by sampling the space of $\mathcal{O}\left(2^n\right)$ bit strings. Conceptually, this can be viewed as a “compression” of the information in the QPF algorithm, which enables period finding from $n$ one-qubit marginals. Our results motivate the development of approximate simulations of reduced density matrices to design period-finding algorithms.

The second law of thermodynamics, quantitatively formalized through non-negative entropy production, defines the fundamental constraints on energy conversion, such as the Carnot limit for heat engines. While it has been suggested that active noises in heat baths might allow microscopic engines to surpass these bounds, such apparent violations often stem from an incomplete thermodynamic accounting of the active reservoir. Here, we demonstrate theoretically and experimentally that the classical second law remains valid when considering active noise as a particle under white Gaussian noise interacting with a Brownian bead, rather than relying on the concept of effective temperature. In this study, our illustrative model system consists of a two-dimensional Brownian gyrator with a bead immersed in temperature baths, combined with active noises. By treating active noise as explicit degrees of freedom, we analytically solve the Langevin equation by decoupling the energetics into two contributions: the interactions of the Brownian bead with the heat baths and with another particle subject to a different heat bath. We find that entropy production is always non-negative; the gyrator can operate as a heat engine in specific environments but cannot surpass the Carnot limit, and the thermodynamic uncertainty relation holds. This study offers a rigorous perspective on the relation between active noise and the second law, demonstrating that properly accounting for active noise as a distinct thermodynamic component preserves the fundamental principles of thermodynamics.

We investigate the dynamics of one-dimensional bright solitonlike state in exciton-polariton condensates under a parity-time (PT) symmetric periodic potential. For the static potential case, we demonstrate the formation of stable gap solitonlike state arising from the combined action of the potential and a composite Gaussian pump. Notably, these gap solitonlike state differ from those in the conventional nonlinear Schrödinger equation in two key ways. First, their existence and stability depend not only on the balance between nonlinearity and dispersion but also critically on the system's gain-loss balance. Second, their profiles (e.g., main-peak amplitude) can be directly controlled by the intensity of the composite Gaussian pump. Furthermore, when the PT-symmetric potential is designed to include a barrier with exponentially varying intensity, we observe that a stable incident bright solitonlike state exhibits controllable switching dynamics, in stark contrast to the unidirectional transmission seen in conservative systems. During this process, the bright solitonlike state transforms into a polariton wave, temporarily disappears, and subsequently re-emerges. This behavior is governed by the interaction between the PT-symmetric barrier and the intrinsic gain-loss mechanism of the system. Additionally, we propose an active control scheme based on nonresonant optical Gaussian pump pulses to precisely manipulate the disappearance time of the bright solitonlike state. Our findings establish a promising platform for soliton-based photonic devices in nonequilibrium systems.

We report on the experimental observation of electron heating in electron-only magnetic reconnection in laser-driven laboratory mini-magnetosphere on the Large Plasma Device (LAPD) at the University of California, Los Angeles. In this experiment, a fast-flowing plasma impacts a pulsed magnetic dipole embedded within LAPD’s magnetized ambient plasma, creating an ion-scale magnetosphere and driving electron-only magnetic reconnection between the background and dipole field lines. The electron velocity distribution is measured across the reconnection region using noncollective Thomson scattering, enabling determination of electron temperature and density. Significant electron heating is observed in the electron diffusion region, increasing from an initial temperature of 1.8 to 9.5 eV, corresponding to a 40% local conversion of Poynting flux into electron enthalpy flux. Particle-in-cell simulations that provide insights into the heating mechanisms are also presented.

First-passage processes are pervasive across numerous scientific fields, yet a general framework for understanding their response to external perturbations remains elusive. While the fluctuation-dissipation theorem offers a complete linear response theory for systems in steady state, it fails to apply to transient first-passage processes. We address this challenge by focusing on rare—rather than weak—perturbations. Surprisingly, we discover that the linear response of the mean first-passage time (MFPT) to such perturbations is universal. It depends solely on the first two moments of the unperturbed first-passage time and the mean completion time following perturbation activation, without any assumptions about the underlying system's dynamics. To demonstrate the utility of our findings, we analyze the MFPT response of drift-diffusion processes in two scenarios: (1) stochastic resetting with information feedback and (2) an abrupt transition from a linear to a logarithmic potential. In both cases, our approach bypasses the need for explicit determination of the perturbed dynamics, unraveling a highly nontrivial response landscape with minimal effort. Finally, we show how our framework enables a new type of experiment—inferring molecular-level fluctuations from bulk measurements, a feat previously believed to be impossible. Overall, the universality reported herein offers a powerful tool for predicting the impact of perturbations on kinetic processes—and, remarkably, for extracting hidden single-molecule fluctuations from accessible bulk measurements.

Stabilizer-based simulation of quantum error-correcting codes typically relies on the Pauli-twirling approximation (PTA) to render non-Clifford noise classically tractable, but PTA can distort the behavior of physically relevant channels such as thermal relaxation. Physically accurate noise simulation is needed to train decoders and understand the noise suppression capabilities of quantum error-correcting codes. In this work, we develop an exact stabilizer model without variance overhead for qubit thermal-relaxation noise when $T_2⩽T_1$. We show that the combined amplitude damping and dephasing channel admits a fully positive Clifford and reset decomposition that enables efficiency in this regime. For $T_2>T_1$, the resulting decomposition is negative, but the same technique serves to reduce the overhead versus independent channels. We further introduce an approximated error channel with reset for the $T_2>T_1$ regime that removes the negativity of the decomposition while achieving higher channel fidelity to the true thermal relaxation than PTA and extend our construction to finite-temperature relaxation. We apply the exact combined model to investigate large surface codes and bivariate bicycle codes on superconducting platforms with realistic thermal-relaxation error. The differing logical performances across code states further indicate that noise-model-informed decoders will be essential for accurately capturing thermal-noise structure in future fault-tolerant architectures.