${\mathrm{Cu}}_3\mathrm{Au}$ experiences a phase transition at 662 K from an ordered low-temperature phase to a disordered solid solution. While significant work has been devoted to characterizing the enthalpy of this transition, the apportionment of the entropy has remained out of reach. Current estimates of the vibrational and configurational entropy for the transition are larger than the total entropy of the transition experimentally measured by calorimetry, while calculations of the electronic entropy via ab initio methods have remained difficult. This work calculates an electronic entropy difference of $-6.29$ J/mol K based on a recent formalism that links experimentally measured electronic transport data and equilibrium thermodynamic properties. The application of this formalism brings some estimates of the vibrational and configurational entropy in line with the calorimetrically measured total entropy.

A periodically modulated $N$-state model whose dynamics are governed by a time-convoluted generalized master equation is theoretically analyzed. It is shown that this non-Markovian master equation can be converted to a Markovian master equation having a larger transition matrix, which affords easier analysis. The behavior of this model is investigated by focusing on the cycle-averaged pumping current. In the adiabatic limit, the geometrical current is calculated analytically and compared with numerical results, which are available for a wide range of modulation frequencies.

In realistic systems of coupled oscillators, it is desired to predict the onset of synchronization where the system equations are unknown, raising the need to develop a prediction framework that is model free and fully data driven. We show that this challenging problem can be addressed with machine learning. In particular, exploiting reservoir computing or echo state networks, we employ a “parameter-aware” scheme to train the neural machine using time series acquired from a small number of distinct asynchronous states in the parameter regime prior to the onset of synchronization. The trained machine can then be used to predict the synchronization transition through tuning the control parameter. We demonstrate the power of the machine learning-based framework using two types of synchronization behaviors: Complete synchronization in coupled identical chaotic oscillators and the phase synchronization in coupled nonidentical phase oscillators, which are representative of the collective dynamics in coupled systems. In addition, we design our numerical experiments such that two transition scenarios are covered: Smooth (second-order) and explosive (first-order) transitions that represent the generic types of phase transition in nonlinear physical systems. A remarkable feature is that, for the network systems exhibiting explosive (first-order) transition, the machine learning scheme is capable of predicting not only the locations of the transition points associated with the forward and backward transition paths but also the hysteresis between the two paths.

Tensor network states are expected to be good representations of a large class of interesting quantum many-body wave functions. In higher dimensions, their utility is however severely limited by the difficulty of contracting the tensor network, an operation needed to calculate quantum expectation values. Here we introduce a method for the time evolution of three-dimensional isometric tensor networks which respects the isometric structure and therefore renders contraction simple through a special canonical form. Our method involves a tetrahedral site splitting which allows one to move the orthogonality center of an embedded tree tensor network in a simple cubic lattice to any position. Using imaginary time evolution to find an isometric tensor network representation of the ground state of the three-dimensional transverse field Ising model across the entire phase diagram, we perform a systematic benchmark study of this method in comparison with exact Lanczos and quantum Monte Carlo results. We show that the obtained energy matches the exact ground-state result accurately deep in the ferromagnetic and polarized phases, while the regime close to the critical point requires larger bond dimensions. This behavior is in close analogy with the two-dimensional case, which we also discuss for comparison.

The role of quantum coherence and correlations in heat flow and equilibration is investigated by exploring the Rayleigh's dynamical problem to equilibration in the quantum regime and following Onsager's approach to thermoelectricity. Specifically, we consider a qubit bombarded by two-qubit projectiles from a side. For arbitrary collision times and initial states, we develop the master equation for sequential and collective collisions. By deriving the Fokker-Planck equation out of the master equation, we identify the quantum version of the Rayleigh's heat conduction equation. We find that quantum discord and entanglement shared between the projectiles can contribute to genuine heat flow only when they are associated with so-called heat-exchange coherences. Analogous to Onsager's use of Rayleigh's principle of least dissipation of energy, we use the entropy production rate to identify the coherence current. Both coherence and heat flows can be written in the form of quantum Onsager relations, from which we predict coherent Peltier and coherent Seebeck effects. The effects can be optimized by the collision times and collectivity. Finally, we discuss some of the possible experimental realizations and technological applications of the thermocoherent phenomena in different platforms.

We discuss a quantum Kolmogorov-Sinai entropy defined as the entropy production per unit time resulting from coupling the system to a weak, auxiliary bath. The expressions we obtain are fully quantum but require that the system is such that there is a separation between the Ehrenfest and the correlation timescales. We show that they reduce to the classical definition in the semiclassical limit, one instance where this separation holds. We show a quantum (Pesin) relation between this entropy and the sum of positive eigenvalues of a matrix describing phase-space expansion. Generalizations to the case where entropy grows sublinearly with time are possible.

Attosecond pulses can ionize atoms in a coherent process. Since the emerging fragments are entangled, however, each preserves only a fraction of the initial coherence, thus limiting the chance of guiding the ion subsequent evolution. In this work, we use ab initio simulations of pump-probe ionization of helium above the $2s/2p$ threshold to demonstrate how this loss of coherence can be controlled. Thanks to the participation of $2\ell n{\ell }^{\prime }$ states, coherence between the ionic $2s$ and $2p$ states, which are degenerate in the nonrelativistic limit, results in a stationary, delay-dependent electric dipole. From the picosecond real-time beating of the dipole, caused by the fine-structure splitting of the $n=2$ manifold, it is possible to reconstruct all original ion coherences, including between antiparallel-spin states, which are a sensitive probe of relativistic effects in attosecond photoemission.

We observed a humplike feature in Hall effects of ${\mathrm{SrRuO}}_3$ ultrathin films, and systematically investigated it by controlling thicknesses, temperatures and magnetic fields. The humplike feature is extremely stable, even surviving as a magnetic field is tilted by as much as ${85}^{\circ }$. Based on the atomic-level structural analysis of a ${\mathrm{SrRuO}}_3$ ultrathin film with a theoretical calculation, we reveal that atomic rumplings at the thin-film surface enhance Dzyaloshinskii-Moriya interaction, which can generate stable chiral spin textures and a humplike Hall effect. Moreover, temperature dependent resonant x-ray measurements at the Ru $L$ edge under a magnetic field showed that the intensity modulation of unexpected peaks was correlated with the hump region in the Hall effect. We verify that the two-dimensional property of ultrathin films generates stable noncoplanar spin textures having a magnetic order in a ferromagnetic oxide material.

Plasmonic vapor nanobubbles are currently considered for a wide variety of applications ranging from solar energy harvesting and photoacoustic imaging to nanoparticle-assisted cancer therapy. Yet, due to their small size and unstable nature, their generation and consequences remain difficult to characterize. Here, building on a phase-field model, we report on the existence of strong pressure waves that are emitted when vapor nanobubbles first form around a laser-heated nanoparticle immersed in water and subsequently after bubble rebound. These effects are strongest when the fluid is locally brought high in its supercritical state, which may be realized with a short laser pulse. Because of the greatly out-of-equilibrium nature of nanobubble generation, the waves combine a high-pressure peak with a fast pressure rising time and propagate in water over micron distances, opening the way to induce spatially and temporally localized damage. Discussing the consequences on biological cell membranes, we conclude that acoustic-mediated perforation is more efficient than nanobubble expansion to breach the membrane. Our findings should serve as a guide for optimizing the thermoacoustic conversion efficiency of plasmonic vapor nanobubbles.

The key idea behind the renormalization group (RG) transformation is that properties of physical systems with very different microscopic makeups can be characterized by a few universal parameters. However, finding a systematic way to construct RG transformation for particular systems remains difficult due to the many possible choices of the weight factors in the RG procedure. Here we show, by identifying the conditional distribution in the restricted Boltzmann machine and the weight factor distribution in the RG procedure, that a valid real-space RG transformation can be learned without prior knowledge of the physical system. This neural Monte Carlo RG algorithm allows for direct computation of the RG flow and critical exponents. Our results establish a solid connection between the RG transformation in physics and the deep architecture in machine learning, paving the way for further interdisciplinary research.

The fast and accessible verification of nonclassical resources is an indispensable step toward a broad utilization of continuous-variable quantum technologies. Here, we use machine learning methods for the identification of nonclassicality of quantum states of light by processing experimental data obtained via homodyne detection. For this purpose, we train an artificial neural network to classify classical and nonclassical states from their quadrature-measurement distributions. We demonstrate that the network is able to correctly identify classical and nonclassical features from real experimental quadrature data for different states of light. Furthermore, we show that nonclassicality of some states that were not used in the training phase is also recognized. Circumventing the requirement of the large sample sizes needed to perform homodyne tomography, our approach presents a promising alternative for the identification of nonclassicality for small sample sizes, indicating applicability for fast sorting or direct monitoring of experimental data.

Quantification of coherence lies at the heart of quantum information processing and fundamental physics. Exact evaluation of coherence measures generally needs a full reconstruction of the density matrix, which becomes intractable for large-scale multipartite systems. Here, we propose a systematic theoretical approach to efficiently estimating lower and upper bounds of coherence in multipartite states. Under the stabilizer formalism, the lower bound is determined by the spectrum estimation method with a small number of measurements, and the upper bound is determined by a single measurement. We verify our theory with a four-qubit optical quantum system. We experimentally implement various multiqubit entangled states, including the Greenberger-Horne-Zeilinger state, the cluster state, and the W state, and show how their coherences are efficiently inferred from measuring a few observables.

The development of direct probes of entanglement is integral to the rapidly expanding field of complex quantum materials. Here we test the robustness of entangled neutrons as a quantum probe by measuring the Clauser-Horne-Shimony-Holt contextuality witness while varying the beam properties. Specifically, we show that the mode entanglement of the spin and path subsystems of individual neutrons prepared in two different experiments using two different apparatuses persists even after varying the entanglement length, coherence length, and neutron energy difference of the paths. The two independent apparatuses acting as entangler-disentangler pairs are static-field magnetic Wollaston prisms and resonance-field radio-frequency flippers. Our results show that the spatial and energy properties of the neutron beam may be significantly altered without reducing the contextuality witness value below the Tsirelson bound, meaning that maximum entanglement is preserved. We also show that two paths may be considered distinguishable even when the path states significantly overlap. Therefore, we have shown that our experimental results are consistent with the distinguishable subsystem assumption down to a separation of less than 100 nm, proving entanglement and the contextual nature of reality on short length scales. This work is the key step in the realization of the modular, robust technique of entangled neutron scattering, which can extract entanglement information from a sample without the knowledge of the microscopic sample Hamiltonian: only semiquantitative knowledge of the correlation lengths of the relevant degrees of freedom and the timescales of the characteristic dynamics is required.

Interfaces limiting two phases in driven systems may exhibit rich dynamical behaviors. Optically induced phase transitions are of particular interest for the study of interfacial phenomena. Dye-doped liquid crystals offer an ideal scenario in which phase transitions can be induced by purely optical means. Light-driven interface dynamics and spatial structure have been partially unveiled. Here we report the emergence of fingerlike structures at the nematic-isotropic interface in a photoisomerization experiment. A reduced model reveals the instability origin, which is derived from a model for the dopant concentration and the order parameter. Analogously to the hydrodynamically triggered finger instability, the interdigital space follows a power law. When the cell is in the isotropic phase and the light turns off, transient foamlike and labyrinthine textures are observed. Numerical simulations reproduce the observed behaviors. Our findings open an avenue for optically addressed interfacial dynamics and shape tailoring of spatial textures, not only liquid crystals but also polymers.

A rope laid on the ground with one end subjected to time-dependent forcing is proposed as a prototypical elastic dynamical contact problem, which we study analytically, numerically, and experimentally. The dynamics is governed by an infinite set of linear and nonlinear resonances. In the limit of weak bending stiffness, the fundamental frequency is found to be independent of the rope tension. A transition between a radiation-less and a wave radiating state occurs via a series of grazing bifurcations, whereby new contacts between the rope and the ground are formed. The grazing bifurcations form overlapping Arnold tongues in the frequency-amplitude parameter space. Finally, for ropes with large bending stiffness and when the geometric nonlinearity is important, bistability is observed between several wave-making regimes.

The presence of edge modes at the interface of two perturbed honeycomb photonic crystals with $C_6$ symmetry is often attributed to the different signs of Berry curvature at the K and ${\mathrm{K}}^{\prime }$ valleys. In contrast to the electronic counterpart, the Chern number defined in photonic valley Hall effect is not a quantized quantity but can be tuned to a finite value including zero simply by changing geometrical perturbations. Here, we argue that the edge modes in photonic valley Hall effect can exist even when Berry curvature vanishes. We numerically demonstrate the presence of the zero-Berry-curvature edge modes in triangular-lattice photonic crystal slab structures in which $C_3$ symmetry is maintained but the inversion symmetry is broken. We investigate the evolution of the Berry curvature from the honeycomb-lattice slab structure to the triangular-lattice photonic crystal slab and show that the triangular-lattice photonic crystals still support edge modes in a very wide photonic band gap. We find that the edge modes with zero Berry curvature can propagate with extremely low bending loss along the interface formed by the triangular-lattice photonic crystals.

Understanding strongly interacting quantum matter and quantum gravity are both important open issues in theoretical physics, and the holographic duality between quantum field theory and gravity theory nicely brings these two topics together. Nevertheless, direct connections between gravity physics and experimental observations in quantum matter are still rare. Here we utilize the gravity physics picture to understand quench dynamics experimentally observed in a class of random spin models realized in several different quantum systems, where the dynamics of magnetization are measured after the external polarization field is suddenly turned off. Two universal features of the magnetization dynamics, namely, a slow decay described by a stretched exponential function and an oscillatory behavior, are respectively found in different parameter regimes across different systems. This paper addresses the issues of generic conditions under which these two universal features can occur, and we find that a natural answer to this question emerges in the gravity picture. By the holographic duality bridged by a model proposed by Maldacena and Qi, the quench dynamics after suddenly turning off the external polarization field is mapped to disconnecting an eternal traversable wormhole. Our studies show that insight from gravity physics can help unifying different experiments in quantum systems.

Multi-plane light conversion (MPLC) allows to perform arbitrary transformations on a finite set of spatial modes with no theoretical restriction to the quality of the transformation. Even though the number of shaped modes is in general small, the number of modes transmitted by an MPLC system is extremely large. In this paper, we aim to characterize the transmission properties of a multi-plane light converter inside and outside the design-modes subspace. We report the construction of the full transmission matrix of such systems. By performing singular value decompositions, we individuate ways to evaluate their efficiency in performing the design transformation. Moreover, we develop an analytical random matrix model that suggests that in the regime of a large number of shaped modes an MPLC system behaves like a random scattering medium with limited number of controlled channels.

The manipulation of topologically protected field configurations such as skyrmions, merons, and antimerons, already predicted and experimentally observed in noncentrosymmetric magnets, could definitely have potential applications in logic gate operations as carriers of information. Here, we present and elaborate a proof of concept on how to construct a three-input noncanonical majority gate on a kagome ferromagnet lacking inversion symmetry. By taking advantage of the existence of edge modes in a kagome magnet, it is possible to create topological excitations such as merons and antimerons at the edge of the material. Using atomistic spin dynamics simulations, we determine the precise physical conditions for the creation and annihilation of merons and antimerons and, in a second stage, we describe the majority gate functionality.

The human cortex is never at rest but in a state of sparse and noisy neural activity that can be detected at broadly diverse resolution scales. It has been conjectured that such a state is best described as a critical dynamical process—whose nature is still not fully understood—where scale-free avalanches of activity emerge at the edge of a phase transition. In particular, some works suggest that this is most likely a synchronization transition, separating synchronous from asynchronous phases. Here, by investigating a simplified model of coupled excitable oscillators describing the cortex dynamics at a mesoscopic level, we investigate the possible nature of such a synchronization phase transition. Within our modeling approach we conclude that—in order to reproduce all key empirical observations, such as scale-free avalanches and bistability, on which fundamental functional advantages rely—the transition to collective oscillatory behavior needs to be of an unconventional hybrid type, with mixed features of type-I and type-II excitability, opening the possibility for a particularly rich dynamical repertoire.