Multifunctional Magnetoelectric Materials for Device Applications

Mutiferroics are a novel class of next generation multifunctional materials, which display simultaneous magnetic spin, electric dipole, and ferroelastic ordering, and have drawn increasing interest due to their multi-functionality for a variety of device applications. Since single-phase materials exist rarely in nature with such cross-coupling properties, an intensive research activity is being pursued towards the discovery of new single-phase multiferroic materials and the design of new engineered materials with strong magneto-electric (ME) coupling. This review article summarizes the development of different kinds of multiferroic material: single-phase and composite ceramic, laminated composite, and nanostructured thin films. Thin-film nanostructures have higher magnitude direct ME coupling values and clear evidence of indirect ME coupling compared with bulk materials. Promising ME coupling coefficients have been reported in laminated composite materials in which signal to noise ratio is good for device fabrication. We describe the possible applications of these materials

Magnetic Effects on Dielectric and Polarization Behavior of Multiferroic Hetrostructures

PbZr0.52Ti0.48O3/La0.67Sr0.33MnO3(PZT/LSMO) bilayer with surface roughness ~ 1.8 nm thin films have been grown by pulsed laser deposition on LaAlO3(LAO) substrates. High remnant polarization (30-54 micro C/cm2), dielectric constant(400-1700), and well saturated magnetization were observed depending upon the deposition temperature of the ferromagnetic layer and applied frequencies. Giant frequency-dependent change in dielectric constant and loss were observed above the ferromagnetic-paramagnetic temperature. The frequency dependent dielectric anomalies are attributed to the change in metallic and magnetic nature of LSMO and also the interfacial effect across the bilayer; an enhanced magnetoelectric interaction may be due to the Parish-Littlewood mechanism of inhomogeneity near the metal-dielectric interface.Comment: 9 pages, 4 figure

Pricing Software Upgrades: The Role of Product Improvement & User Costs

The computer software industry is an extreme example of rapid new product introduction. However, many consumers are sophisticated enough to anticipate the availability of upgrades in the future. This creates the possibility that consumers might either postpone purchase or buy early on and never upgrade. In response, many software producers offer special upgrade pricing to old customers in order to mitigate the effects of strategic consumer behavior. We analyze the optimality of upgrade pricing by characterizing the relationship between magnitude of product improvement and the equilibrium pricing structure, particularly in the context of user upgrade costs. This upgrade cost (such as the cost of upgrading complementary hardware or drivers) is incurred by the user when she buys the new version but is not captured by the upgrade price for the software. Our approach is to formulate a game theoretic model where consumers can look ahead and anticipate prices and product qualities while the firm can offer special upgrade pricing. We classify upgrades as minor, moderate or large based on the primitive parameters. We find that at sufficiently large user costs, upgrade pricing is an effective tool for minor and large upgrades but not moderate upgrades. Thus, upgrade pricing is suboptimal for the firm for a middle range of product improvement. User upgrade costs have both direct and indirect effects on the pricing decision. The indirect effect arises because the upgrade cost is a critical factor in determining whether all old consumers would upgrade to a new product or not and this further alters the product improvement threshold at which special upgrade pricing becomes optimal. Finally, we also analyze the impact of upgrade pricing on the total coverage of the market

Usage-based pricing of software services under competition

With the emergence of high speed networks, software firms have the ability to deploy ‘software as a service\u27 and measure resource usage at the level of individual customers. This enables the implementation of usage-based pricing. We study both fixed and usage-based pricing schemes in a competitive setting where the firm incurs a transaction cost of monitoring usage if it implements usage-based pricing. Offering different pricing schemes helps to differentiate the firms and relax price competition, particularly at higher monitoring costs, even when competing firms offer the same service quality. However, the low usage customers acquired by offering usage-based pricing are unable to compensate for the monitoring costs incurred. This implies that managers should be cautious about implementing usage-based pricing in a competitive setting

A Compact Noise-Tolerant Algorithm for Unbiased Quantum Simulation Using Feynman's iηi\eta Prescription

Quantum simulation advantage over classical memory limitations would allow compact quantum circuits to yield insight into intractable quantum many-body problems. But the interrelated obstacles of large circuit depth in quantum time evolution and noise seem to rule out unbiased quantum simulation in the near term. We prove that Feynman's $i\eta$ prescription exponentially improves the circuit depth needed for quantum time evolution. We apply the prescription to the construction of a hybrid classical/quantum algorithm to estimate a useful observable, energy gap. We prove the algorithm's tolerance to all common Markovian noise channels. We demonstrate the success and limitations of the algorithm by using it to perform unbiased finite-size scaling of the transverse field Ising model using an IBMQ device and related noise models. Our findings set the stage for unbiased quantum gap estimation on machines where non-Markovian noise is kept below tolerances.Comment: 14 pages, 10 figures, 2 table