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A happy marriage between critical phenomena and spintronics (Vol. 49, No. 3)
Spintronics is a technology that aims to use spin in information processing for practical application, whereas critical phenomena belong to an academic subject that deals with phase transition. These two seemingly different subfields meet at the interface between a magnetic insulator and a paramagnetic metal. The thermal spin injection from an insulating magnet into the adjacent heavy metal is referred to as spin Seebeck effect. Since its discovery in 2008, this phenomenon has attracted much attention as a simple and versatile means for generating spin current that is needed to drive the functionality of spintronic devices. The spin Seebeck effect has been investigated extensively over the last few years, but only a little is known about its behaviour near the magnetic phase transition.
Using a stochastic model established through the study of dynamic critical phenomena, the authors have investigated the behavior of the spin Seebeck effect near the Curie temperature Tc of a simple ferromagnet which is composed of a single sublattice such as EuO. They have clarified theoretically that the spin Seebeck signal scales with the magnetization, i.e., ~(T-Tc)1/2. Because no corresponding experiments have been reported so far, the theoretical prediction awaits experimental proof.
H. Adachi, Y. Yamamoto and M. Ichioka, Spin Seebeck effect in a simple ferromagnet near Tc: a Ginzburg–Landau approach, J. Phys. D: Appl. Phys. 51, 144001 (2018)
[Abstract]
Rare events in “noisy” networks (Vol. 49, No. 3)
Bringing diseases to extinction and mitigating the effects of human-caused environmental changes which accelerate the rate of species extinction are issues of worldwide importance. Both phenomena are typically rare events, relying on the interplay between network topology, nonlinear dynamics, and random fluctuations from the environment and interactions. However, the prediction of such rare events in general stochastic networks was an unsolved problem, despite extensive work in network dynamics. Here we solve the problem of predicting rare events as large fluctuations from metastable states with a general theory that combines mean-field approximations, large-deviation techniques and network topology. A benefit of our approach is its flexibility in describing the effects of multiple sources of different continuous and discrete noise. Using our theory, we demonstrate that networks with both internal interaction noise and external parameter noise exhibit a cross-over where the familiar exponential scaling of rare-event times with the number of nodes in the network is lost, and parametric noise dominates.
J. Hindes and I. B. Schwartz, Rare events in networks with internal and external noise, EPL 120, 56004 (2017)
[Abstract]
Approximate quantum cloning: the new way of eavesdropping in quantum cryptography (Vol. 49, No. 3)
Credit Markus Spiske via Unsplash
New approximate cloning method avoids the previous limitations of quantum cloning to enhance quantum computing and quantum cryptography leaks
Cloning of quantum states is used for eavesdropping in quantum cryptography. It also has applications in quantum computation based on quantum information distribution. Uncertainty at the quantum scale makes exact cloning of quantum states impossible. Yet, they may be copied in an approximate way—with a certain level of probability—using a method called probabilistic quantum cloning, or PQC. In a new study published recently, the authors demonstrate that partial PQC of a given quantum state secretly chosen from a certain set of states, which can be expressed as the superposition of the other states, is possible. This cloning operation is very important with regard to classical computing. It allows scientists to make many copies of the output of computations—which take the form of unitary operations. These can, in turn, be used as input and fed into various further processes. In quantum computing, for example, previous studies have shown that PQC can help to enhance performance compared to alternative methods. This means that when unitary operations generate some linearly-dependent states, partial PQC can be helpful.
P. Rui, W. Zhang, Y. Liao and Z. Zhang, Probabilistic quantum cloning of a subset of linearly dependent states, Eur. Phys. J. D 72, 26 (2018)
[Abstract]
Non-Stationary Noise with Memory in Josephson Junctions (Vol. 49, No. 3)
In addition to the non-dissipative supercurrent, Josephson junctions also possess a dissipative memristive current component, meaning that the instantaneous resistance of the junction depends on the history of the current. Devices that display this exotic behavior are currently under intense study due to possible applications ranging from fast, high-density, nonvolatile computer memories to neuromorphic computing. In a previous work, the authors suggested a novel device to isolate this current component and thus realize a superconducting memristor. In this work the manifestation of the memristive behaviour in the current noise is considered. The presence of memory renders this noise non-stationary. The authors theoretically characterize both the thermal noise and the 'dynamic'-noise arising across a biased junction, using a mixed time-frequency description. A way to detect this effect of the memristive behaviour on the current noise is also proposed, which should be feasible with current experimental tools.
F. Sheldon, S. Peotta and M. Di Ventra, Phase-dependent noise in Josephson junctions, Eur. Phys. J. Appl. Phys. 81, 10601 (2018)
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