Immigrant women’s entrepreneurship: is there a development model in Italy?

The aim of this paper is to verify if there is a typical enterprise model for the development of immigrant female entrepreneurship in Italy. Based on the literature on the subject, however, it is useful to ask the following research question: “can membership in a national and international network facilitate the development of immigrant female entrepreneurship operating in Italy”? The survey was carried out by submitting a questionnaire to a sample of immigrant women entrepreneurs in the textile and clothing sector based in Italy. The choice fell on this specific economic segment because it represents the third largest sector for the number of female immigrant entrepreneurs (2.271 units) which amounts to 16% of the total number of entrepreneurs operating in the same sector. The percentage of respondents was 35%, with 795 completed questionnaires. The structure of the questionnaire reflects the need to examine the personal features of female entrepreneurs, the organizational aspects and the style of leadership, the task environment in which the enterprise works and the main possible benefits, or obstacles, they might obtain, or face. In addition to the objective of enlarging the literature regarding the management and governance of businesses run by women entrepreneurs, that is quite limited to date, this paper is a contribution to the analysis of a possible development model of women entrepreneurs

Development perspectives of relational capital in women-led firms

The purpose of the paper is to analyze the strategic role of relational capital for the achievement of sustainable development in Italian micro and small tourist businesses run by women. The paper focuses on the tourism enterprises because that sector constitute 10 % of the Italian GDP. The qualitative research methodology that has been used is that of case study research (Yin, 2009). Such process consisted in a survey with an ad-hoc questionnaire developed to analyze the distinctive features of a woman-owned micro and small enterprise that can be identified with the CAOS model (Paoloni, 2011). The paper applies the CAOS model examining the personal characteristics of the female entrepreneur (C); the environment in which the in SMEs operates (A); organizational and managerial aspects (O); and the motivations for manage a new business (S). This model is able to link these factors and classify different types of connections, it is possible to identify the kind of existing relations. The paper intends to help address a gap in the existing literature regarding the management and governance of tourism firms run by women. The paper can contribute to improving the competitiveness Italian enterprises studying how women entrepreneurs manage her business

Experimental multiphase estimation on a chip

Multiparameter estimation is a general problem that aims at measuring unknown physical quantities, obtaining high precision in the process. In this context, the adoption of quantum resources promises a substantial boost in the achievable performances with respect to the classical case. However, several open problems remain to be addressed in the multiparameter scenario. A crucial requirement is the identification of suitable platforms to develop and experimentally test novel efficient methodologies that can be employed in this general framework. We report the experimental implementation of a reconfigurable integrated multimode interferometer designed for the simultaneous estimation of two optical phases. We verify the high-fidelity operation of the implemented device, and demonstrate quantum-enhanced performances in two-phase estimation with respect to the best classical case, post-selected to the number of detected coincidences. This device can be employed to test general adaptive multiphase protocols due to its high reconfigurability level, and represents a powerful platform to investigate the multiparameter estimation scenario.Comment: 10+7 pages, 7+4 figure

Integrated sources of entangled photons at telecom wavelength in femtosecond-laser-written circuits

Photon entanglement is an important state of light that is at the basis of many protocols in photonic quantum technologies, from quantum computing, to simulation and sensing. The capability to generate entangled photons in integrated waveguide sources is particularly advantageous due to the enhanced stability and more efficient light-crystal interaction. Here we realize an integrated optical source of entangled degenerate photons at telecom wavelength, based on the hybrid interfacing of photonic circuits in different materials, all inscribed by femtosecond laser pulses. We show that our source, based on spontaneous parametric down-conversion, gives access to different classes of output states, allowing to switch from path-entangled to polarization-entangled states with net visibilities above 0.92 for all selected combinations of integrated devices

Adaptive phase estimation through a genetic algorithm

Quantum metrology is one of the most relevant applications of quantum information theory to quantum technologies. Here, quantum probes are exploited to overcome classical bounds in the estimation of unknown parameters. In this context, phase estimation, where the unknown parameter is a phase shift between two modes of a quantum system, is a fundamental problem. In practical and realistic applications, it is necessary to devise methods to optimally estimate an unknown phase shift by using a limited number of probes. Here we introduce and experimentally demonstrate a machine learning-based approach for the adaptive estimation of a phase shift in a Mach-Zehnder interferometer, tailored for optimal performances with limited resources. The employed technique is a genetic algorithm used to devise the optimal feedback phases employed during the estimation in an offline fashion. The results show the capability to retrieve the true value of the phase by using few photons, and to reach the sensitivity bounds in such small probe regime. We finally investigate the robustness of the protocol with respect to common experimental errors, showing that the protocol can be adapted to a noisy scenario. Such approach promises to be a useful tool for more complex and general tasks where optimization of feedback parameters is required

Photonic Quantum Metrology

Quantum Metrology is one of the most promising application of quantum technologies. The aim of this research field is the estimation of unknown parameters exploiting quantum resources, whose application can lead to enhanced performances with respect to classical strategies. Several physical quantum systems can be employed to develop quantum sensors, and photonic systems represent ideal probes for a large number of metrological tasks. Here we review the basic concepts behind quantum metrology and then focus on the application of photonic technology for this task, with particular attention to phase estimation. We describe the current state of the art in the field in terms of platforms and quantum resources. Furthermore, we present the research area of multiparameter quantum metrology, where multiple parameters have to be estimated at the same time. We conclude by discussing the current experimental and theoretical challenges, and the open questions towards implementation of photonic quantum sensors with quantum-enhanced performances in the presence of noise.Comment: 51 pages, 9 figures, 967 references. Comments and feedbacks are very welcom

Air-core fiber distribution of hybrid vector vortex-polarization entangled states

Entanglement distribution between distant parties is one of the most important and challenging tasks in quantum communication. Distribution of photonic entangled states using optical fiber links is a fundamental building block towards quantum networks. Among the different degrees of freedom, orbital angular momentum (OAM) is one of the most promising due to its natural capability to encode high dimensional quantum states. In this article, we experimentally demonstrate fiber distribution of hybrid polarization-vector vortex entangled photon pairs. To this end, we exploit a recently developed air-core fiber which supports OAM modes. High fidelity distribution of the entangled states is demonstrated by performing quantum state tomography in the polarization-OAM Hilbert space after fiber propagation, and by violations of Bell inequalities and multipartite entanglement tests. The present results open new scenarios for quantum applications where correlated complex states can be transmitted by exploiting the vectorial nature of light

Deep reinforcement learning for quantum multiparameter estimation

Estimation of physical quantities is at the core of most scientific research, and the use of quantum devices promises to enhance its performances. In real scenarios, it is fundamental to consider that resources are limited, and Bayesian adaptive estimation represents a powerful approach to efficiently allocate, during the estimation process, all the available resources. However, this framework relies on the precise knowledge of the system model, retrieved with a fine calibration, with results that are often computationally and experimentally demanding. We introduce a model-free and deep-learning-based approach to efficiently implement realistic Bayesian quantum metrology tasks accomplishing all the relevant challenges, without relying on any a priori knowledge of the system. To overcome this need, a neural network is trained directly on experimental data to learn the multiparameter Bayesian update. Then the system is set at its optimal working point through feedback provided by a reinforcement learning algorithm trained to reconstruct and enhance experiment heuristics of the investigated quantum sensor. Notably, we prove experimentally the achievement of higher estimation performances than standard methods, demonstrating the strength of the combination of these two black-box algorithms on an integrated photonic circuit. Our work represents an important step toward fully artificial intelligence-based quantum metrology