Quantum logic gates from time-dependent global magnetic field in a system with constant exchange

Abstract

We propose a method for implementation of an universal set of one-and two-quantum-bit gates for quantum computation in the system of two coupled electrons with constant non-diagonal exchange interaction. Suppression of the exchange interaction is offered to implement by all-the-time repetition of single spin rotations. Small g-factor difference of electrons allows to address qubits and to avoid strong magnetic field pulses. It is shown by means of numerical experiments that for implementation of one-and two-qubit operations it is sufficient to change the amplitude of the magnetic field within a few Gauss, introducing in a resonance one and then the other electron. To find the evolution of the two-qubit system, we use the algorithms of the optimal control theory.

A π-shaped quantum device for implementation of Bell states in solid state environment

“…To extract these exchange pairs, magnetic or semiconductor (SC) o/p leads can be used. The use of SC contacts as o/p leads will serve the purpose of avoiding possibility of spin de-phasing [42][43][44][45]. Fabrication of thin channel can lead to interesting effects such as the Coulomb Blockade effect which may allow few electrons to enter into the channel thus, allowing efficient spin injection.…”

Crosstalk error correction through dynamical decoupling of single-qubit gates in capacitively coupled singlet-triplet semiconductor spin qubits

“…The magnetic field difference is realized using a micromagnet or by polarizing the nuclei (if possible). This difference may in principle also be realized by electrically tuning the effective g factors in the quantum dots [37][38][39] , but this technique has not been used in any singlet-triplet qubit experiment to date. It is very difficult to control this field difference quickly in the actual experiments, and thus it is held constant.…”

Three Search Algorithms for Three Nonconvex Optimization Problems

“…It is necessary to stochastically select a starting point or a search direction to increase the probability of finding the global extremum. In complex applied problems, it is still difficult to talk about the guarantee of achieving the global extremum in any nonconvex optimization problem, but research is actively performed (see, for example, [1]- [3]) and the developed algorithms are applied in practice [4,5].…”