About two decades ago quantum computing (QC) was introduced with a promise to the solution of many unmanageable problems (Ruggiero, 2005). Experiments related to a small group of qubits using Nuclear Magnetic Resonance (NMR) showed that QC can be done (Keyes, 2003). After the arrival of powerful algorithms for quantum computation; efforts are made to implement these devices physically. According to research, two qubits (the basic element of a quantum computer) interactions were ample for quantum algorithm implementation (Keyes, 2003). It was proved that a scalable physical system with qubits which is initializable to a simple fiducial state, with longer decoherence time and composed of a universal set of quantum gates that allows high quantum efficiency measurements, can be a candidate for implementation of QC (DiVincenzo, 2000). NMR with molecules is bound to ten qubits whereas a useful quantum computer would need more. To achieve this, solid-state technology is the easiest way (Keyes, 2003).
In early 2000, the solid-state QC in its infancy showed only the simplest quantum logical operation with a hope for scalable architectures. This newly emerging field at that time could take advantage of the research meant for the progress of smaller and faster logical devices (Kane, 2003). There are difficulties in integrating qubits into solid-state systems because of the fact that the necessary decoupling required for QC is hard to achieve because 1023 atoms are present in a solid-state device. Recently, research is more concentrating on superconducting qubits where quantum information is stored on flux states in a SQUID or in semiconductors on electron or nuclear spin qubits. Also coding the quantum information repeatedly into several qubits can lessen the errors along with correction in quantum computation (Kane, 2003).
Shahriar et al. (2000) made research in the field of solid-state QC by using spectral holes. There are two spatial methods to deal qubits; focusing a laser beam on individual qubit or spectral method where nuclear spin in a molecule is dealt with using NMR. A method combining spatial and spectral selectivity to deal with qubits leads to a design for quantum computation with a capacity for quantum information storage and processing higher order magnitudes than ion traps or NMR. The method is described in the following fig.2.
Moving forward in the research of solid-state QC, the problem of decoherence and design found a solution with comprehensive encoding and decoupling. The practical solution to the mentioned problem is dealt by first reducing decoherence by encoding a logical qubit into two qubits and subsequently eradicated by an efficient set of sequence of decoupling pulse. The unmanageable design constraint due to the single qubit operations is also dealt with the help of this encoding (Byrd and Lidar, 2002). Also to optimize the decoupling pulses, the controlling decoherence processes can be identified by trial and error.
According to De-Rinaldis et al., (2002), GaN based quantum dots are the basic building blocks of solid-state QC devices. As an application to solid-state QC the intrinsic exciton-exciton coupling in GaN based quantum dots was achieved. The creation of a high strength built-in electric field, caused by the self-generated polarization and by the piezoelectricity, is used to generate entangled few exciton states in coupled quantum dots without recurring to the external fields. Also the induction of intrinsic exciton-exciton coupling by the built in field was part of the research. This led to the realization of basic quantum information processing on a time scale of sub-picoseconds.
According to a research nano-structured logic gates can be used for solid-state QC and quantum dot devices (Eriksson, 2003). Here the semiconductor dot devices are made up of aggregated semiconductor structure that consists of a substrate, a layer of back gate electrode, and a layer of quantum well, a layer of tunnel barrier which lies between the quantum well and the back gate layer and a barrier layer above the quantum well layer. Multiple electrode gates are created on the multiple layer semi-conductors having the gates separated from each other by an area below which quantum dots may be defined. Suitable voltages applied to the electrodes permits the development and suitable positioning of the quantum dots, permitting a huge quantity of quantum dots to be created in a series with suitable coupling between the dots. Performing QC is also possible without the g-factor tuning and the individual spin rotations through high frequency radiation which g-factor tuning permits. Alternatively, the time-dependent exchange interaction, H(t) = J(t)S1.S2, can be employed by combining it with the coded qubits.
Quantum computing predicts a way to handle some intractable problems of digital computing. Quantum computers that are developed with diverse methods of solid-state technology to formulate qubits are interesting because the large number of devices required for these computers could be formed with well established technologies. Still the imperfections of solid-state devices developed in laboratories will confine their use in QC. One such problem was revealed during an influential proposal for a quantum computer in silicon where the system used existing silicon IC technology for placing an array of spin ½ phosphorous donor atoms a little distance beneath the surface of a substrate of silicon (Keyes, 2005). Nuclei of phosphorous serves as qubits and the applied magnetic field determines two distinct states for the spins of electrons that the phosphorous atom’s positive charge catches thus interaction of field and electrons influencing the nuclei by the link between the electron wave function and the nucleus. Devices created by solid-state technology use planar surfaces where adjacent qubits on a surface may act towards other qubits on that surface by the overlapping functions or with a capacitive link. Mostly the experiments of qubits that are successful have made use of superconducting devices. One such example is the experiment that used a superconducting Coulomb box as the qubit (Keyes, 2005).
In a latest research by Hujun et al., (2008) the authors have considered the single electron transistors for solid-state qubit measurements by dealing with the continuous weak measurement of a solid-state qubit through single electron transistor (SET). It was found that in nonlinear response regime universal upper bound imposed quantum can be exceeded by the signal-to-noise ratio mechanically on any linear response detector. Also the strong constitution of double dot SET as opposed to wider range of temperatures, quantum efficiency and the applicable open issues were left undecided.
The creation and detailed analysis of highly optimized self refocusing pulse shapes for various rotation angles was presented by Pryadko and Sengupta, (2008) calling it the second order shaped pulses for solid-state quantum computation. Description of the constructed pulses with the help of appearing coefficients in the Magnus expansion up to second order which permits a semi analytical analysis of the functioning of these constructed shapes in a sequence and the complex pulses with the help of computing the similar leading order error operators. In a previous technique higher orders can also be analyzed while here the technique was demonstrated by the analysis of several composite pulses that are designed to guard against pulse amplitude errors and on decoupling sequences capable of long chains of qubits that have on the scene and nearest neighbour couplings as shown in fig.3.
In a recent research issues related to practical implementation of QC like scalability, switching of coupling interaction and decoherence free behaviour were addressed (Ruda and Qiao, 2003). A few approaches for implementation of solid-state were brought-in where one of the best was the silicon based nuclear spin or electron spin computers. Still the recognition of these schemes is dependent on the future technology for implementation of nanostructures (Ruggiero, 2005). Here a new approach for fabricating large scale lattices of nanostructures was demonstrated but again the implementation on QC is dependent on future technology. Ruda and Qiao (2003) has discussed the problem of decoherence and the use of error avoiding approaches. More precisely a novel scheme based on sub-dynamics was presented and a bright future for solid-state QC was predicted provided the architecture and control strategies are suitable.