The nonequilibrium dynamics of light in a coherently driven nonlinear cavity resembles the equilibrium dynamics of a Brownian particle in a scalar potential. This resemblance has been known for decades, but the correspondence between the two systems has never been properly assessed. Here we demonstrate that this correspondence can be exact, be approximate, or break down, depending on the driving conditions. For vanishing nonlinearity and on-resonance driving, the correspondence is exact: The cavity dissipation and driving amplitude define a scalar potential, and light follows the equilibrium Boltzmann distribution with an effective temperature defined by the noise variance and cavity dissipation. The scalar potential pertaining to linear on-resonance dynamics fails dramatically in nonlinear and/or off-resonance regimes. However, we introduce a distinct scalar potential enabling an effective equilibrium description of light. Our potential gives a reasonably accurate description in limited nonlinear regimes of bistability, but fails deep in the bistability where nonconservative forces dominate the dynamics. Consequently, the correspondence to Brownian motion in a scalar potential breaks down. This breakdown is accompanied by a qualitative change in the spectrum of small intracavity field fluctuations, reminiscent of an exceptional point of a non-Hermitian Hamiltonian. Our results lay the foundations for an effective thermodynamic description of coherently driven cavities, and suggest that fundamental results for overdamped Langevin dynamics can help to assess the energetics and information processing of resonant optical technologies.

Modification of optical phonon spectra in contacting nonpolar nanoparticles compared to single particles is studied. Optical phonons in dielectric and semiconducting particles obey the Euclidean metric Klein-Fock-Gordon equation with Dirichlet boundary conditions. This equation is supposed to be solved numerically for manifolds of cojoined spheres. It is proposed to replace this problem with the simpler-to-solve coupled-oscillator model (COM), where an oscillator is attributed to each phonon mode of a particle and the particle overlap leads to the appearance of additional couplings for these oscillators with the magnitude proportional to the overlap volume. For not too big overlaps, this model describes solutions of the original eigenvalue problem with a quantitative level of accuracy. In particular, it works beyond isotropic $s$ modes in dimers, which has been demonstrated for $p$ modes in dimers and for tetramers. It is proposed to apply the COM for the description of recently manufactured dimer nanoparticles and quantum dots. The obtained results are in agreement with the dynamical matrix method for optical phonons in nanodiamonds. The dynamical matrix method is also used to demonstrate that the van der Waals contacts between faceted particles lead to very small modifications of the optical phonon spectra, which therefore could be neglected when discussing the propagation of vibrational excitations via a nanopowder. The possibility to distinguish between dimerized and size-distributed single particles from their Raman spectra is also considered. The proposed COM paves a way towards the description of propagation of vibrational modes in the ensembles of particles in contact including tight agglomerates, nanocrystal solids, and porous media.

A method from random-matrix theory is used to calculate the pair correlation function of a one-dimensional gas of $N\gg 1$ classical particles with a power-law repulsive interaction potential $u\left(x\right)\propto {\left|x\right|}^{-s}$ (a so-called Riesz gas). An integral formula for the covariance of single-particle operators is obtained, which generalizes known results in the limits $s\to -1$ (Coulomb gas) and $s\to 0$ (log-gas). As an application, we calculate the variance of the center of mass of the Riesz gas, which has a universal large-$N$ limit that does not depend on the shape of the confining potential.

The influence of measurement back action on electro-optic sampling of electromagnetic quantum fluctuations is investigated. Based on a cascaded treatment of the nonlinear interaction between a near-infrared coherent probe and the mid-infrared vacuum, we account for the generated electric-field contributions that lead to detectable back action. Specifically, we theoretically address two realistic setups, exploiting one or two probe beams for the nonlinear interaction with the quantum vacuum, respectively. The setup parameters at which back action starts to considerably contaminate the measured noise profiles are determined. We find that back action starts to detrimentally affect the signal once the fluctuations due to the coupling to the mid-infrared vacuum become comparable to the base shot noise. Due to the vacuum fluctuations entering at the beam splitter, the shot noise of two incoming probe pulses in different channels is uncorrelated. Therefore, even when the base shot noise dominates the output of the experiment, it does not contribute to the correlation signal itself. However, we find that further contributions due to nonlinear shot-noise enhancement are still present. Ultimately, a regime in which electro-optic sampling of quantum fields can be considered as effectively back-action free is found.

Cold atoms hold much promise for the realization of quantum technologies, but still encounter many challenges. In this work we show how the fundamental Casimir-Polder force, by which atoms are attracted to a surface, may be temporarily suppressed by utilizing a specially designed quantum potential, which is familiar from the hydrodynamic or Bohmian reformulations of quantum mechanics. We show that when harnessing the quantum potential via suitable atomic wave-packet engineering, the absorption by the surface can be dramatically reduced. As a result, the probing time of the atoms as sensors can increase. This is proven both analytically and numerically. Furthermore, an experimental scheme is proposed for achieving the required shape for the atomic wave packet. All these may assist existing applications of cold atoms in metrology and sensing and may also enable prospective ones. Finally, these results shed light on the notion of quantum potential and its significance.

Dusty plasmas represent a powerful platform to study the collective dynamics of strongly coupled systems with important interdisciplinary connections to condensed matter physics. Due to the pure Yukawa repulsive interaction between dust particles, dusty plasmas do not display a traditional liquid-vapor phase transition, perfectly matching the definition of a supercritical fluid. Using molecular dynamics simulations, we verify the supercritical nature of dusty plasmas and reveal the existence of a dynamical liquidlike to gaslike crossover which perfectly matches the salient features of the Frenkel line in classical supercritical fluids. We present several diagnostics to locate this dynamical crossover spanning from local atomic connectivity, shear relaxation dynamics, velocity autocorrelation function, heat capacity, and various transport properties. All these different criteria well agree with each other and are able to successfully locate the Frenkel line in both 2D and 3D dusty plasmas. In addition, we propose the unity ratio of the instantaneous transverse sound speed $C_T$ to the average particle speed ${\overline{v}}_p$, i.e., $C_T/{\overline{v}}_p=1$, as a diagnostic to identify this dynamical crossover. Finally, we observe an emergent degree of universality in the collective dynamics and transport properties of dusty plasmas as a function of the screening parameter and dimensionality of the system. Intriguingly, the temperature of the dynamical transition is independent of the dimensionality and it is found to always be 20 times of the corresponding melting point. Our results open a path for the study of single particle and collective dynamics in plasmas and their interrelation with supercritical fluids in general.

We consider a typical circuit QED setup where an artificial atom encodes a qubit and is dispersively coupled to a measurement resonator that in turn is coupled to a transmission line. We show theoretically that by placing another artificial atom in this transmission line to act as a filter, the Purcell decay of the qubit into the transmission line is suppressed. When strong control fields are applied in the transmission line, the filter is saturated and effectively switched off. Such a Purcell filtering capability permits both the control and measurement of the qubit using the single transmission line, while maintaining the long coherence time of the qubit in the absence of the control pulses. We show that high fidelity Pauli ${\sigma }_x$ gates on the qubit can be realized using simple pulse shapes. For devices that already use one transmission line both for control and measurement of the qubit, our paper provides a way to completely filter out the qubit frequency without removing the possibility of controlling the system. Further, combining the proposed filter with frequency multiplexing potentially enables both control and measurement of several qubits using a single Purcell-filtered transmission line. This will enhance the scalability of superconducting quantum processors by decreasing the number of the required transmission lines.

The ultrafast and element-specific response of magnetic systems containing ferromagnetic $3d$ transition metals and $4d/5d$ heavy metals is of interest both from a fundamental as well as an applied research perspective. However, to date no consensus about the main microscopic processes describing the interplay between intrinsic $3d$ and induced $4d/5d$ magnetic moments upon femtosecond laser excitation exist. In this work we study the ultrafast response of CoFeB/Pt bilayers by probing element-specific, core-to-valence-band transitions in the extreme ultraviolet spectral range using high harmonic radiation. We show that the combination of magnetic scattering simulations and analysis of the energy- and time-dependent magnetic asymmetries allows us to accurately disentangle the element-specific response in spite of overlapping Co and Fe ${\mathit{M}}_{2,3}$ as well as Pt ${\mathit{O}}_{2,3}$ and ${\mathit{N}}_7$ resonances. We find a considerably smaller demagnetization time constant as well as much larger demagnetization amplitudes of the induced moment of Pt compared to the intrinsic moment of CoFeB. Our results are in agreement with enhanced spin-flip probabilities due to the high spin-orbit coupling localized at the heavy metal Pt, as well as with the recently formulated hypothesis that a laser-generated, incoherent magnon population within the ferromagnetic film leads to an overproportional reduction of the induced magnetic moment of Pt.

We introduce and analytically illustrate that hitherto unexplored imaginary components of out-of-time order correlators can provide unprecedented insight into the information scrambling capacity of a graph neural network. Furthermore, we demonstrate that it can be related to conventional measures of correlation like quantum mutual information and rigorously establish the inherent mathematical bounds (both upper and lower bound) jointly shared by such seemingly disparate quantities. To consolidate the geometrical ramifications of such bounds during the dynamical evolution of training we thereafter construct an emergent convex space. This newly designed space offers much surprising information including the saturation of lower bound by the trained network even for physical systems of large sizes, transference, and quantitative mirroring of spin correlation from the simulated physical system across phase boundaries as desirable features within the latent subunits of the network (even though the latent units are directly oblivious to the simulated physical system) and the ability of the network to distinguish exotic spin connectivity (volume law vs area law). Such an analysis demystifies the training of quantum machine learning models by unraveling how quantum information is scrambled through such a network introducing correlation surreptitiously among its constituent subsystems and open a window into the underlying physical mechanism behind the emulative ability of the model.

Quantum processors have the potential to accelerate specific computing tasks but are difficult to scale up due to engineering limitations, such as the number of available cables and cooling power for dilution refrigerators for quantum bits (qubits). Hence, it is very important to develop scalable, energy-efficient interface circuits that can control many qubits via a few control lines inside a dilution refrigerator. One of the most important interface circuits is the flux controller (FC), which generates arbitrary dc flux bias to adjust the characteristics of component devices such as qubits. In this paper, we propose and demonstrate FCs using an energy-efficient superconductor logic family, adiabatic quantum-flux-parametron (AQFP) logic. We develop two types of FCs: the AQFP FC and the AQFP/single-flux-quantum (AQFP/SFQ) FC. Both FCs require only a few control lines and have extremely small power dissipation, thus exhibiting high scalability. Furthermore, the AQFP/SFQ FC can control flux bias using ballistic SFQ transmission, which is crucial for integration with qubits. As a proof of concept, we demonstrate AQFP and AQFP/SFQ FCs at 4.2 K, fabricated by the AIST high-speed standard process. Our results indicate that AQFP logic is highly suitable for use as qubit interface circuits for very large-scale quantum processors, especially from the viewpoint of the control line count, power dissipation, and amount of supply currents.

A wave propagating through a scattering medium typically yields a complex temporal field distribution. Over the years, a number of procedures have emerged to shape the temporal profile of the field in order to temporally focus its energy on a receiver. By analogy, we theoretically and experimentally demonstrate here how to maximize the total Fisher information transmitted to a receiver, and how to focus the Fisher information at any given time. This enables one to estimate small variations in the value of any physical observable with optimal precision from noisy measurements, as experimentally illustrated using acoustic waves in the ultrasound regime. By yielding the ultimate precision limit achievable from time-resolved measurements performed in arbitrarily complex media, our approach sets a general benchmark for many applications such as structural health monitoring and biomedical imaging.

We use the normal mode formalism to study the shear rheology of the vertex model for epithelial tissue mechanics in the overdamped linear response regime. We consider systems with external (e.g., cell-substrate) and internal (e.g., cell-cell) dissipation mechanisms, and derive expressions for stresses on cells due to mechanical and dissipative forces. The semi-analytical method developed here is, however, general and can be directly applied to study the linear response of a broad class of soft matter systems with internal and external dissipation. It involves normal mode decomposition to calculate linear loss and storage moduli of the system. Specifically, displacements along each normal mode produce stresses due to elastic deformation and internal dissipation, which are in force balance with loads due to external dissipation. Each normal mode responds with a characteristic relaxation timescale, and its rheological behavior can be described as a combination of a standard linear solid element due to elastic stresses and a Jeffreys model element due to the internal dissipative stresses. The total response of the system is then fully determined by connecting in parallel all the viscoelastic elements corresponding to individual normal modes. This allows full characterization of the potentially complex linear rheological response of the system at all driving frequencies and identification of collective excitations. We show that internal and external dissipation mechanisms lead to qualitatively different rheological behaviors due to the presence or absence of Jeffreys elements, which is particularly pronounced at high driving frequencies. Our findings, therefore, underscore the importance of microscopic dissipation mechanisms in understanding the rheological behavior of soft materials and tissues, in particular.

The orbital angular momentum (OAM) of light is an infinite-dimensional degree of freedom of light with several applications in both classical and quantum optics. However, to fully take advantage of the potential of OAM states, reliable detection platforms to characterize generated states in experimental conditions are needed. Here, we present an approach to reconstruct input OAM states from measurements of the spatial intensity distributions they produce. To obviate issues arising from intrinsic symmetry of Laguerre-Gauss modes, we employ a pair of intensity profiles per state projecting it only on two distinct bases, showing how this allows to uniquely recover input states from the collected data. Our approach is based on a combined application of dimensionality reduction via principal component analysis, and linear regression, and thus has a low computational cost during both training and testing stages. We showcase our approach in a real photonic setup, generating up-to-four-dimensional OAM states through quantum walk dynamics. The high performance and versatility of the demonstrated approach make it an ideal tool to characterize high-dimensional states in quantum information protocols.

Molecular topology of polymers plays a key role in determining their physical properties. We studied herein the topological effects on the static and dynamic properties of a 2D catenated network of DNA rings called a kinetoplast. Restriction enzymes that cleave DNA at sequence-specific sites are used to selectively cut and remove rings from the network and hence tune the molecular topology while maintaining overall structural integrity. We find that topology has minimal effects over the spatial extension of the 2D network; however, it significantly affects the relaxation behavior. The shape fluctuations of the network are governed by two distinct characteristic time scales attributed to the thermal fluctuations and confinement of the network. The relationship between the time constant of thermal relaxation and the amplitude of anisotropy fluctuations yields a universal scaling. Interestingly, this scaling is independent of the detailed arrangements of rings and/or perforation within the catenated networks. This study provides a route to tune the elastic properties of 2D catenated DNA networks and other polymeric materials by modifying the underlying topology in a rational and highly controllable manner.

Quantum machine learning represents a promising approach to disclose novel possibilities for quantum information protocols. Thus, recent efforts have been dedicated to determine how to merge, or extend, machine learning approaches in the quantum domain. A relevant example is provided by a quantum-optical neural network (QONN), a class of physical systems that aim to represent the quantum-optical version of classical neural networks. This architecture was first introduced to identify the structure of optical circuits in analogy to their classical counterpart, showing the possibility of tackling different quantum tasks. However, the full potential of such an approach still needs to be explored. In this work, we provide a step forward in this direction by employing it to tackle the fundamental task of optical quantum cloning. The employed architecture has been successfully trained to perform deterministic universal quantum cloning on a photonic platform, achieving results that are very close to that of an optimal universal quantum cloner. Furthermore, we have verified numerically the robustness of this approach with respect to experimental imperfections relevant for future implementations. This work thus shows the capabilities and flexibility of QONNs, which might prove important for designing even more complex optical circuits.

Relevant metrological scenarios involve the simultaneous estimation of multiple parameters. The fundamental ingredient to achieve quantum-enhanced performance is based on the use of appropriately tailored quantum probes. However, reaching the ultimate resolution allowed by physical laws requires nontrivial estimation strategies from both a theoretical and a practical point of view. A crucial tool for this purpose is the application of adaptive learning techniques. Indeed, adaptive strategies provide a flexible approach to obtain optimal parameter-independent performance and optimize convergence to the fundamental bounds with a limited amount of resources. Here, we combine on the same platform quantum-enhanced multiparameter estimation attaining the corresponding quantum limit and adaptive techniques. We demonstrate the simultaneous estimation of three optical phases in a programmable integrated photonic circuit, in the limited-resource regime. The obtained results show the possibility of successfully combining different fundamental methodologies towards transition to quantum sensors applications.

We study the conditions necessary for the onset of liquid-liquid crystalline phase separation (LLCPS) in a system of dynamically evolving amyloid fibrils whose kinetics is controlled by nucleation, growth and fragmentation. In the case of thin, rigid rods, the volume fraction does not influence the emergence of LLCPS, which is always possible. Beyond the constraints imposed by rigid rods, for semiflexible fibrils, LLCPS stems out instead from a trade-off between the contour and persistence length. Fibrils fragmentation affects LLCPS in a similar manner by delaying the concentration needed for LLCPS onset.