Frequency shifting with a solid-state switching capacitor

Frequency shifting, commonly used in electronic signal processing, is applied in tuning, automatic frequency control, antenna element switching, phase shifting, etc. Frequency shifting can be accomplished economically and reliably with simple circuit comprising conventional resistor and solid-state switching device which can be equivalent to two capacitors, depending on switching state

Antiferromagnetic cavity optomagnonics

Currently there is a growing interest in studying the coherent interaction between magnetic systems and electromagnetic radiation in a cavity, prompted partly by possible applications in hybrid quantum systems. We propose a multimode cavity optomagnonic system based on antiferromagnetic insulators, where optical photons couple coherently to the two homogeneous magnon modes of the antiferromagnet. These have frequencies typically in the THz range, a regime so far mostly unexplored in the realm of coherent interactions, and which makes antiferromagnets attractive for quantum transduction from THz to optical frequencies. We derive the theoretical model for the coupled system, and show that it presents unique characteristics. In particular, if the antiferromagnet presents hard-axis magnetic anisotropy, the optomagnonic coupling can be tuned by a magnetic field applied along the easy axis. This allows us to bring a selected magnon mode into and out of a dark mode, providing an alternative for a quantum memory protocol. The dynamical features of the driven system present unusual behavior due to optically induced magnon-magnon interactions, including regions of magnon heating for a red-detuned driving laser. The multimode character of the system is evident in a substructure of the optomagnonically induced transparency window

Composite metal-oxide device has voltage sensitive capacitance

Device with step function variation of the capacitance is useful for voltage-controlled oscillator circuits and as a voltage-sensitive switch. Simplicity of construction makes the device suitable for large-scale integration, microelectronic circuits

Bits from Biology for Computational Intelligence

Computational intelligence is broadly defined as biologically-inspired computing. Usually, inspiration is drawn from neural systems. This article shows how to analyze neural systems using information theory to obtain constraints that help identify the algorithms run by such systems and the information they represent. Algorithms and representations identified information-theoretically may then guide the design of biologically inspired computing systems (BICS). The material covered includes the necessary introduction to information theory and the estimation of information theoretic quantities from neural data. We then show how to analyze the information encoded in a system about its environment, and also discuss recent methodological developments on the question of how much information each agent carries about the environment either uniquely, or redundantly or synergistically together with others. Last, we introduce the framework of local information dynamics, where information processing is decomposed into component processes of information storage, transfer, and modification -- locally in space and time. We close by discussing example applications of these measures to neural data and other complex systems

Insider Action research as an approach and a method – Exploring institutional encounters from within a birthing context

The aim of this paper was to describe the first person perspective of being a peer midwife and a novice researcher initiating collaborative AR in her own organization to develop knowledge about the first encounters between the labouring woman and her care-givers in a hospital birthing context. It was motivated by the author’s longstanding professional clinical experience of observing and hearing parents’ stories of vulnerability and fear of childbirth, and how staff’s attitudes affected the childbirth experience negatively. Data were collected between 2010 and 2013 and included the researcher’s log with reflections from clinical work, as well as interviews, participant observation, and research group communications. A reflective interpretative lifeworld research approach was used to analyze the data. The experience of being a novice insider action researcher (IARr) consisted of three thematic meanings: ‘‘the struggle to initiate a clinical insider action research project,’’ ‘‘standing alone at the messy front line,’’ and ‘‘being a catalytic counterbalance to the prevailing medico technical focus.’’ The comprehensive understanding was ‘‘learning how to clinically reflect on and to voice the tacit components of care.’’ The strategy used in undertaking this study was influenced by the philosophies of both midwifery care and AR

Partial Information Decomposition as a Unified Approach to the Specification of Neural Goal Functions

In many neural systems anatomical motifs are present repeatedly, but despite their structural similarity they can serve very different tasks. A prime example for such a motif is the canonical microcircuit of six-layered neo-cortex, which is repeated across cortical areas, and is involved in a number of different tasks (e.g.sensory, cognitive, or motor tasks). This observation has spawned interest in finding a common underlying principle, a 'goal function', of information processing implemented in this structure. By definition such a goal function, if universal, cannot be cast in processing-domain specific language (e.g. 'edge filtering', 'working memory'). Thus, to formulate such a principle, we have to use a domain-independent framework. Information theory offers such a framework. However, while the classical framework of information theory focuses on the relation between one input and one output (Shannon's mutual information), we argue that neural information processing crucially depends on the combination of \textit{multiple} inputs to create the output of a processor. To account for this, we use a very recent extension of Shannon Information theory, called partial information decomposition (PID). PID allows to quantify the information that several inputs provide individually (unique information), redundantly (shared information) or only jointly (synergistic information) about the output. First, we review the framework of PID. Then we apply it to reevaluate and analyze several earlier proposals of information theoretic neural goal functions (predictive coding, infomax, coherent infomax, efficient coding). We find that PID allows to compare these goal functions in a common framework, and also provides a versatile approach to design new goal functions from first principles. Building on this, we design and analyze a novel goal function, called 'coding with synergy'. [...]Comment: 21 pages, 4 figures, appendi

Generalized Entanglement as a Natural Framework for Exploring Quantum Chaos

We demonstrate that generalized entanglement [Barnum {\em et al.}, Phys. Rev. A {\bf 68}, 032308 (2003)] provides a natural and reliable indicator of quantum chaotic behavior. Since generalized entanglement depends directly on a choice of preferred observables, exploring how generalized entanglement increases under dynamical evolution is possible without invoking an auxiliary coupled system or decomposing the system into arbitrary subsystems. We find that, in the chaotic regime, the long-time saturation value of generalized entanglement agrees with random matrix theory predictions. For our system, we provide physical intuition into generalized entanglement within a single system by invoking the notion of extent of a state. The latter, in turn, is related to other signatures of quantum chaos.Comment: clarified and expanded version accepted by Europhys. Let

Mixing in Non-Quasirandom Groups

We initiate a systematic study of mixing in non-quasirandom groups. Let A and B be two independent, high-entropy distributions over a group G. We show that the product distribution AB is statistically close to the distribution F(AB) for several choices of G and F, including: 1) G is the affine group of 2x2 matrices, and F sets the top-right matrix entry to a uniform value, 2) G is the lamplighter group, that is the wreath product of ?? and ?_{n}, and F is multiplication by a certain subgroup, 3) G is H? where H is non-abelian, and F selects a uniform coordinate and takes a uniform conjugate of it. The obtained bounds for (1) and (2) are tight. This work is motivated by and applied to problems in communication complexity. We consider the 3-party communication problem of deciding if the product of three group elements multiplies to the identity. We prove lower bounds for the groups above, which are tight for the affine and the lamplighter groups

Shaken Granular Lasers

Granular materials have been studied for decades, also driven by industrial and technological applications. These very simple systems, composed by agglomerations of mesoscopic particles, are characterized, in specific regimes, by a large number of metastable states and an extreme sensitivity (e.g., in sound transmission) on the arrangement of grains; they are not substantially affected by thermal phenomena, but can be controlled by mechanical solicitations. Laser emission from shaken granular matter is so far unexplored; here we provide experimental evidence that it can be affected and controlled by the status of motion of the granular, we also find that competitive random lasers can be observed. We hence demonstrate the potentialities of gravity affected moving disordered materials for optical applications, and open the road to a variety of novel interdisciplinary investigations, involving modern statistical mechanics and disordered photonics.Comment: 4 pages, 3 figures. To be published in Physical Review Letter