Optical rogue waves emerge as the optical analogue to oceanic rogue waves, namely as a temporally rare fluctuations characterized by exceptionally high intensities. The authors observe the emergence and the real-time dynamics of such intensity bursts undergoing nonlinear spatial transformation in spatiotemporally mode-locked fiber lasers.

Optomechanics deals with the control and applications of mechanical effects of light on matter. Here, these effects on single-material and multimaterial larger particles with size ranging from 20 nm to a 1 μm are investigated in proximity of epsilon-near-zero metamaterials exploiting different theoretical methods.

There have been recent studies reporting that Mn-doped MAPBI₃ houses a ferromagnetic phase mediated by a double exchange mechanism. Here, however, using X-ray magnetic circular dichroism and magnetic susceptibility measurements, the authors uncover contradicting experimental evidence to indicate an absence of magnetic ordering in this material, suggesting that our understanding of Mn-doped lead halide perovskites may need reassessing.

Quantum Monte Carlo (QMC) techniques have been very successful in quantum simulation. This paper shows a pathway to provide orders of magnitude speedup to QMC simulations through massively parallel architectures (both digital and mixed signal) while maintaining a scaling advantage over QMC implemented in software.

The description of organic semiconductors relies on a series of approximations, resulting in an uncertain and fragmented picture of the charge transport processes. The authors combine numerical and analytical quantum approaches to study three distinct charge transfer regimes and the transitions between them in a consistent picture.

Ultrafast spectroscopy allows for the real-time observation of molecular processes and enables a better understanding of the electron dynamics and nuclear evolution that occur during a chemical reaction. Here, the authors study, experimentally and theoretically, the electron localization that occurs on a femtosecond timescale during the dissociation of N₂O.

Realizing quantum conference key agreement is challenging in experiment and unpractical in application because of limited transmission distance caused by channel loss. The authors present here a quantum conference key agreement protocol with spatial multiplexing nature and adaptive operation, which can break limitations on quantum communication over network and thus shed some light on future global quantum network.

The generation of entanglement in qubit-oscillator systems is often hindered by low-intensity driving fields, and limited control of qubit-oscillator coupling. The authors design a general method to achieve robust entanglement gates using low-intensity dynamical-decoupling pulses with non-tuneable qubit-oscillator coupling.

Chimera states of coupled oscillators have been the subject of considerable interest in complex nonlinear systems. The authors experimentally observe chimera states in a photonic spiking neural network of identical neurons with homogeneous interactions, suggesting that the system with high controllability provides a novel platform to researching synchronous phenomena.

Particle track fitting in dense detectors is crucial for understanding particle kinematics. The authors show how deep learning outperforms traditional Bayesian filtering methods, drastically improving the reconstruction of interacting particles and potentially impacting the design and data exploitation of future particle physics experiments.

Kerr optical frequency combs are extensively explored for their potential capabilities in fields such optical communication, spectroscopy, and sensing. This work theoretically analyses the role of phase noise in comb generation dynamics through a stochastic approach, which can impact future studies of frequency comb sources.

Quantum machine learning studies the application of concepts and techniques originating in machine learning to quantum devices. In this paper, the authors develop a framework to model quantum extreme learning machines, showing that they can be concisely described via single effective measurements, and provide an explicit characterization of the information that can be exactly retrieved using such protocols.

Scaling-up quantum key distribution to large distances, although imperative for realizing a globally secure quantum internet, inevitably suffers from polarization fluctuations. This work demonstrates an alternative approach to resource intensive active polarization tracking in mitigating the said challenge, by optimizing measurement bases at the receiver end.