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Quantum optical networks are instrumental to address fundamental questions and enable applications ranging from communication to computation and, more recently, machine learning. In particular, photonic artificial neural networks offer the opportunity to exploit the advantages of both classical and quantum optics. Photonic neuro-inspired computation and machine learning have been successfully demonstrated in classical settings, while quantum optical networks have triggered breakthrough applications such as teleportation, quantum key distribution and quantum computing. We present a perspective on the state of the art in quantum optical machine learning and the potential advantages of artificial neural networks in circuit designs and beyond, in more general analogue settings characterised by recurrent and coherent complex interactions. We consider two analogue neuro-inspired applications, namely quantum reservoir computing and quantum associative memories, and discuss the enhanced capabilities offered by quantum substrates, highlighting the specific role of light squeezing in this context.

Associative memory refers to the ability to relate a memory with an input and targets the restoration of corrupted patterns. It has been intensively studied in classical physical systems, as in neural networks where an attractor dynamics settles on stable solutions. Several extensions to the quantum domain have been recently reported, displaying different features. In this work, we develop a comprehensive framework for a quantum associative memory based on open quantum system dynamics, which allows us to compare existing models, identify the theoretical prerequisites for performing associative memory tasks, and extend it in different forms. The map that achieves an exponential increase in the number of stored patterns with respect to classical systems is derived. We establish the crucial role of symmetries and dissipation in the operation of quantum associative memory. Our theoretical analysis demonstrates the feasibility of addressing both quantum and classical patterns, orthogonal and non-orthogonal memories, stationary and metastable operating regimes, and measurement-based outputs. Finally, this opens up new avenues for practical applications in quantum computing and machine learning, such as quantum error correction or quantum memories.

We conduct a numerical investigation of fiber-based entanglement distribution over distances of up to 1600km using a chain of processing-node quantum repeaters. We determine minimal hardware requirements while simultaneously optimizing over protocols for entanglement generation and entanglement purification, as well as over strategies for entanglement swapping. Notably, we discover that through an adequate choice of protocols the hardware improvement cost scales linearly with the distance covered. Our results highlight the crucial role of good protocol choices in significantly reducing hardware requirements, such as employing purification to meet high-fidelity targets and adopting a SWAP-ASAP policy for faster rates. To carry out this analysis, we employ an extensive simulation framework implemented with NetSquid, a discrete-event-based quantum-network simulator, and a genetic-algorithm-based optimization methodology to determine minimal hardware requirements.

Quantum oscillators with nonlinear driving and dissipative terms have gained significant attention due to their ability to stabilize cat-states for universal quantum computation. Recently, superconducting circuits have been employed to realize such long-lived qubits stored in coherent states. We present a generalization of these oscillators, which are not limited to coherent states, in the presence of different nonlinearities in driving and dissipation, exploring different degrees. Specifically, we present an extensive analysis of the asymptotic dynamical features and of the storage of squeezed states. We demonstrate that coherent superpositions of squeezed states are achievable in the presence of a strong symmetry, thereby allowing for the storage of squeezed cat-states. In the weak symmetry regime, accounting for linear dissipation, we investigate the potential application of these nonlinear driven-dissipative resonators for quantum computing and quantum associative memory and analyze the impact of squeezing on their performance.

Algorithms for associative memory typically rely on a network of many connected units. The prototypical example is the Hopfield model, whose generalizations to the quantum realm are mainly based on open quantum Ising models. We propose a realization of associative memory with a single driven-dissipative quantum oscillator exploiting its infinite degrees of freedom in phase space. The model can improve the storage capacity of discrete neuron-based systems in a large regime and we prove successful state discrimination between $n$ coherent states, which represent the stored patterns of the system. These can be tuned continuously by modifying the driving strength, constituting a modified learning rule. We show that the associative-memory capacity is inherently related to the existence of a spectral gap in the Liouvillian superoperator, which results in a large timescale separation in the dynamics corresponding to a metastable phase.

In this article we study the galactic evolution of the LiBeB elements within the framework of a detailed model of the chemical evolution of the Galaxy that includes galactic cosmic ray nucleosynthesis by particles accelerated in superbubbles. The chemical composition of the superbubble consists of varying proportions of ISM and freshly supernova synthesized material. The observational trends of 6 LiBeB evolution are nicely reproduced by models in which GCR come from a mixture of 25% of supernova material with 75% of ISM, except for 6 Li, for which maybe an extra source is required at low metallicities. To account for 7 Li evolution several additional sources have been considered (neutrino-induced nucleosynthesis, nova outbursts, C-stars). The model fulfills the energetic requirements for GCR acceleration., Comment: 25 pages, 9 figures. Accepted for publication in the Astrophysical Journal

We extend our model of chemical evolution that successfully account for the main observables in the solar neighborhood (Alibes, Labay & Canal 2001) to the whole Milky Way halo and disk. We assume an inside-out scenario for the assembling of the Galaxy through the infall of external material. Two different compositions of the infalling material have been considered: primordial and slightly metal-enriched (0.1 Z_{\sun}). Our calculations follow the evolution of 76 isotopes up to the Iron peak, but we only present here results for the elements having well-measured gradients: C, N, O, Ne, Mg, Al, Si, S, Ar and Fe. The calculated current radial distributions of these elements are compared with large samples of data from HII regions, B stars, planetary nebulae and open clusters. We also discuss the time evolution of the abundance gradients. Good fits are achieved with both infall compositions, closer to the observational data in the case of primordial infall. We show that contributions from intermediate-mass stars allow to reproduce the measured abundances of C and N, but the profiles of their ratios to oxygen leave still open the nucleosynthetic origin of these elements. In agreement with several previous works, our models predict a flattening with time of the abundance gradients, most of which taking place during the early galactic evolution., Comment: 16 pages, 11 figures, submitted to A&A

A LiBeB evolution model including Galactic Cosmic Ray nucleosynthesis, the $\nu$-process, novae, AGB and C-stars is presented. We have included Galactic Cosmic Ray Nucleosynthesis (GCRN) in a complete Chemical Evolution Model that takes into account 76 stable isotopes from hydrogen to zinc. Any successful LiBeB evolution model should also be compatible with other observational constraints like the age-metallicity relation, the G-dwarf distribution or the evolution of other elements. At the same time, we have checked how different would be a model that took into account the last observations by Wakker et al. (1999) of metal-enriched clouds falling onto the disk, from a primordial infall model., Comment: 2 pages, 2 figures. To appear in `Cosmic Evolution' Conference at IAp, Paris 13-17 Nov 2000

We have developed a detailed standard chemical evolution model to study the evolution of all the chemical elements up to the iron peak in the solar vicinity. We consider that the Galaxy was formed through two episodes of exponentially decreasing infall, out of extragalactic gas. In a first infall episode, with a duration of $\sim$ 1 Gyr, the halo and the thick disk were assembled out of primordial gas, while the thin disk formed in a second episode of infall of slightly enriched extragalactic gas, with much longer timescale. The model nicely reproduces the main observational constraints of the solar neighborhood, and the calculated elemental abundances at the time of the solar birth are in excellent agreement with the solar abundances. By the inclusion of metallicity dependent yields for the whole range of stellar masses we follow the evolution of 76 isotopes of all the chemical elements between hydrogen and zinc. Those results are confronted with a large and recent body of observational data, and we discuss in detail the implications for stellar nucleosynthesis., Comment: 19 pages, 14 figures, submitted to A&A

The SWRL Kindergarten Program was developed by the Southwest Regional Laboratory for Educational Research and Development (SWRL), a federally funded facility located in Inglewood, California. In Birmingham, interest in the SWRL program was stimulated and developed during the Fall of 1971. It was felt that this program would provide the children with an opportunity to be exposed to an early reading program. The components of the SWRL Program consisted of the Instructional Concepts Program (ICP) which was intended to introduce the children to concepts of shape, size, color, amounts, poisitions, and comparisons. Upon completion of the ICP, the Beginning Reading Program (BRP) was initiated. The goals of this program were to teach the children word recognition and the vocabulary of the program design. Some support systems were also developed to aid the children in maintaining or improving their acquired skills. (Author/DEP)

Results of the research reported in this paper suggest that the development of mentally handicapped preschool children may not be measurable in distinct cognitive, social/emotional, physical motor, and language areas. This research further indicates that a testing instrument designed to measure the generalized factors of intelligence and social adaptability in a classroom setting may be sufficient for the identification of the mentally handicapped child prior to his (her) first public school experience. This paper highlights the results of an effort to determine the predictive power of the Wechsler Preschool and Primary Scale of Intelligence (WPPSI), the Denver Developmental Screening Test, the Leiter International Performance Scale, the Southeastern Day Care Project (HEW) Rating Scale, and the ABC Inventory when used to diagnose mentally handicapped children in the areas of preschool cognitive, social/emotional, physical motor, and language development. The specific objective of the research is to determine if mentally handicapped preschool youngsters really need to be tested in all four areas of development in order to accurately predict which children require individual help prior to public school kindergarten placement. (Author/DEP)

A survey of 65 freshman and 195 junior business administration majors in one metropolitan state university investigated student perceptions of institutional attributes salient in college choice. Results suggest standards of institutional quality are difficult to establish, since evaluations of institutional performance are not consistent, even among an undergraduate student population. (Author/MSE)

The involvement of culturally and linguistically diverse parents is critical to meeting the unique educational needs of their children. The main points discussed are effective communication, comfort level of parents, barriers between school and parents, and parental literacy. The goal is ultimately to involve these parents in educational decision making and governance. (TD)