568 research outputs found
A Mixed Methods Study of Environmental Determinants of Entrepreneurship
It wasnât until the 1960s that academic interest emerged to explore the relationship between organizations, such as entrepreneurial firms, and their respective natural environments (Starik & Marcus, 2000). Although the study of entrepreneurship and environmental conditions is a more recent scholarly focus, it continues to gain attention in academic research (Meek et al., 2010). Despite an increasing amount of highquality research throughout the past decade, environmental conditions remain largely underappreciated in management theory (Whiteman & Cooper, 2011). This study complements prior research by exploring the theories surrounding entrepreneurship and environmental conditions. In addition, this study advances the cumulative body of research by analyzing the multilevel determinants of entrepreneurship across environments. Using a mixed methods approach consisting of interviews and cross-sectional data, the results provide a descriptive illustration of the relationship between entrepreneurship and environmental conditions. The qualitative and quantitative findings offer novel insight to help answer the following research question: In what ways do environments influence entrepreneurship
Self-referenced continuous-variable quantum key distribution protocol
We introduce a new continuous-variable quantum key distribution (CV-QKD)
protocol, self-referenced CV-QKD, that eliminates the need for transmission of
a high-power local oscillator between the communicating parties. In this
protocol, each signal pulse is accompanied by a reference pulse (or a pair of
twin reference pulses), used to align Alice's and Bob's measurement bases. The
method of phase estimation and compensation based on the reference pulse
measurement can be viewed as a quantum analog of intradyne detection used in
classical coherent communication, which extracts the phase information from the
modulated signal. We present a proof-of-principle, fiber-based experimental
demonstration of the protocol and quantify the expected secret key rates by
expressing them in terms of experimental parameters. Our analysis of the secret
key rate fully takes into account the inherent uncertainty associated with the
quantum nature of the reference pulse(s) and quantifies the limit at which the
theoretical key rate approaches that of the respective conventional protocol
that requires local oscillator transmission. The self-referenced protocol
greatly simplifies the hardware required for CV-QKD, especially for potential
integrated photonics implementations of transmitters and receivers, with
minimum sacrifice of performance. As such, it provides a pathway towards
scalable integrated CV-QKD transceivers, a vital step towards large-scale QKD
networks.Comment: 14 pages, 10 figures. Published versio
Quantum-assisted quantum compiling
Compiling quantum algorithms for near-term quantum computers (accounting for
connectivity and native gate alphabets) is a major challenge that has received
significant attention both by industry and academia. Avoiding the exponential
overhead of classical simulation of quantum dynamics will allow compilation of
larger algorithms, and a strategy for this is to evaluate an algorithm's cost
on a quantum computer. To this end, we propose a variational hybrid
quantum-classical algorithm called quantum-assisted quantum compiling (QAQC).
In QAQC, we use the overlap between a target unitary and a trainable
unitary as the cost function to be evaluated on the quantum computer. More
precisely, to ensure that QAQC scales well with problem size, our cost involves
not only the global overlap but also the local
overlaps with respect to individual qubits. We introduce novel short-depth
quantum circuits to quantify the terms in our cost function, and we prove that
our cost cannot be efficiently approximated with a classical algorithm under
reasonable complexity assumptions. We present both gradient-free and
gradient-based approaches to minimizing this cost. As a demonstration of QAQC,
we compile various one-qubit gates on IBM's and Rigetti's quantum computers
into their respective native gate alphabets. Furthermore, we successfully
simulate QAQC up to a problem size of 9 qubits, and these simulations highlight
both the scalability of our cost function as well as the noise resilience of
QAQC. Future applications of QAQC include algorithm depth compression,
black-box compiling, noise mitigation, and benchmarking.Comment: 19 + 10 pages, 14 figures. Added larger scale implementations and
proof that cost function is DQC1-har
Variational Quantum Linear Solver
Previously proposed quantum algorithms for solving linear systems of
equations cannot be implemented in the near term due to the required circuit
depth. Here, we propose a hybrid quantum-classical algorithm, called
Variational Quantum Linear Solver (VQLS), for solving linear systems on
near-term quantum computers. VQLS seeks to variationally prepare
such that . We derive an operationally meaningful
termination condition for VQLS that allows one to guarantee that a desired
solution precision is achieved. Specifically, we prove that , where is the VQLS cost function and is the
condition number of . We present efficient quantum circuits to estimate ,
while providing evidence for the classical hardness of its estimation. Using
Rigetti's quantum computer, we successfully implement VQLS up to a problem size
of . Finally, we numerically solve non-trivial problems of size
up to . For the specific examples that we consider, we
heuristically find that the time complexity of VQLS scales efficiently in
, , and the system size .Comment: 13 + 8 pages, 15 figures, 7 table
A Stable Calcium Alumanyl
A seven-membered N,NâČ-heterocyclic potassium alumanyl nucleophile is introduced and utilised in the metathetical synthesis of MgâAl and CaâAl bonded derivatives. Both species have been characterised by experimental and theoretical means, allowing a rationalisation of the greater reactivity of the heavier group 2 species implied by an initial assay of their reactivity.</p
Anthropometric indices of Gambian children after one or three annual rounds of mass drug administration with azithromycin for trachoma control.
BACKGROUND: Mass drug administration (MDA) with azithromycin, carried out for the control of blinding trachoma, has been linked to reduced mortality in children. While the mechanism behind this reduction is unclear, it may be due, in part, to improved nutritional status via a potential reduction in the community burden of infectious disease. To determine whether MDA with azithromycin improves anthropometric indices at the community level, we measured the heights and weights of children aged 1 to 4 years in communities where one (single MDA arm) or three annual rounds (annual MDA arm) of azithromycin had been distributed. METHODS: Data collection took place three years after treatment in the single MDA arm and one year after the final round of treatment in the annual MDA arm. Mean height-for-age, weight-for-age and weight-for-height z scores were compared between treatment arms. RESULTS: No significant differences in mean height-for-age, weight-for-age or weight-for-height z scores were found between the annual MDA and single MDA arms, nor was there a significant reduction in prevalence of stunting, wasting or underweight between arms. CONCLUSIONS: Our data do not provide evidence that community MDA with azithromycin improved anthropometric outcomes of children in The Gambia. This may suggest reductions in mortality associated with azithromycin MDA are due to a mechanism other than improved nutritional status
Multi-channel whole-head OPM-MEG: Helmet design and a comparison with a conventional system
© 2020 The Authors Magnetoencephalography (MEG) is a powerful technique for functional neuroimaging, offering a non-invasive window on brain electrophysiology. MEG systems have traditionally been based on cryogenic sensors which detect the small extracranial magnetic fields generated by synchronised current in neuronal assemblies, however, such systems have fundamental limitations. In recent years, non-cryogenic quantum-enabled sensors, called optically-pumped magnetometers (OPMs), in combination with novel techniques for accurate background magnetic field control, have promised to lift those restrictions offering an adaptable, motion-robust MEG system, with improved data quality, at reduced cost. However, OPM-MEG remains a nascent technology, and whilst viable systems exist, most employ small numbers of sensors sited above targeted brain regions. Here, building on previous work, we construct a wearable OPM-MEG system with âwhole-headâ coverage based upon commercially available OPMs, and test its capabilities to measure alpha, beta and gamma oscillations. We design two methods for OPM mounting; a flexible (EEG-like) cap and rigid (additively-manufactured) helmet. Whilst both designs allow for high quality data to be collected, we argue that the rigid helmet offers a more robust option with significant advantages for reconstruction of field data into 3D images of changes in neuronal current. Using repeat measurements in two participants, we show signal detection for our device to be highly robust. Moreover, via application of source-space modelling, we show that, despite having 5 times fewer sensors, our system exhibits comparable performance to an established cryogenic MEG device. While significant challenges still remain, these developments provide further evidence that OPM-MEG is likely to facilitate a step change for functional neuroimaging
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