scholarly journals Numerical method for determination of the NMR frequency of the single-qubit operation in a silicon-based solid-state quantum computer

2006 ◽  
Vol 74 (19) ◽  
Author(s):  
H. T. Hui
Keyword(s):  
Solid State ◽  
Numerical Method ◽  
Quantum Computer ◽  
Single Qubit ◽  
Silicon Based ◽  
Qubit Operation

scholarly journals A silicon-based surface code quantum computer

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Joe O’Gorman ◽  
Naomi H Nickerson ◽  
Philipp Ross ◽  
John JL Morton ◽  
Simon C Benjamin
Keyword(s):  
Quantum Computing ◽  
Solid State ◽  
Quantum Computer ◽  
Fault Tolerant ◽  
Device Fabrication ◽  
Impurity Atoms ◽  
Dipole Interactions ◽  
Total Phase ◽  
Surface Code ◽  
Silicon Based

Abstract Individual impurity atoms in silicon can make superb individual qubits, but it remains an immense challenge to build a multi-qubit processor: there is a basic conflict between nanometre separation desired for qubit–qubit interactions and the much larger scales that would enable control and addressing in a manufacturable and fault-tolerant architecture. Here we resolve this conflict by establishing the feasibility of surface code quantum computing using solid-state spins, or ‘data qubits’, that are widely separated from one another. We use a second set of ‘probe’ spins that are mechanically separate from the data qubits and move in and out of their proximity. The spin dipole–dipole interactions give rise to phase shifts; measuring a probe’s total phase reveals the collective parity of the data qubits along the probe’s path. Using a protocol that balances the systematic errors due to imperfect device fabrication, our detailed simulations show that substantial misalignments can be handled within fault-tolerant operations. We conclude that this simple ‘orbital probe’ architecture overcomes many of the difficulties facing solid-state quantum computing, while minimising the complexity and offering qubit densities that are several orders of magnitude greater than other systems.

SILICON-BASED NUCLEAR SPIN QUANTUM COMPUTER

2005 ◽  
Vol 03 (supp01) ◽  
pp. 27-40 ◽  
Author(s):  
HSI-SHENG GOAN
Keyword(s):  
Solid State ◽  
Nuclear Spin ◽  
Quantum Computer ◽  
Theoretical Progress ◽  
Spin Quantum ◽  
Basic Physics ◽  
Qubit Operations ◽  
Silicon Based

We review the basic physics and operation principles of the silicon-based quantum computer proposed by Kane, one of the most promising solid-state quantum computer proposals. We describe in some details how single- and two-qubit operations and readout measurements can, in principle, be performed for the Kane quantum computer. In addition, we also mention briefly its recent theoretical progress and development.

Towards the atomic-scale fabrication of a silicon-based solid state quantum computer

2003 ◽  
Vol 532-535 ◽  
pp. 1209-1218 ◽  
Author(s):  
Michelle Y. Simmons ◽  
Steven R. Schofield ◽  
Jeremy L. O’Brien ◽  
Neil J. Curson ◽  
Lars Oberbeck ◽  
...  
Keyword(s):  
Solid State ◽  
Quantum Computer ◽  
Atomic Scale ◽  
Silicon Based

scholarly journals Solid-state Stern–Gerlach spin splitter for magnetic field sensing, spintronics, and quantum computing

2018 ◽  
Vol 9 ◽  
pp. 1558-1563 ◽  
Author(s):  
Kristofer Björnson ◽  
Annica M Black-Schaffer
Keyword(s):  
Solid State ◽  
Magnetic Flux ◽  
Quantum Computer ◽  
Characteristic Size ◽  
Two Dimensional ◽  
Interference Effects ◽  
Switching Field ◽  
Single Qubit ◽  
Field Sensitivity ◽  
Universal Quantum

We show conceptually that the edge of a two-dimensional topological insulator can be used to construct a solid-state Stern–Gerlach spin splitter. By threading such a Stern–Gerlach apparatus with a magnetic flux, Aharanov–Bohm-like interference effects are introduced. Using ferromagnetic leads, the setup can be used to both measure magnetic flux and as a spintronics switch. With normal metallic leads a switchable spintronics NOT-gate can be implemented. Furthermore, we show that a sequence of such devices can be used to construct a single-qubit SU(2)-gate, one of the two gates required for a universal quantum computer. The field sensitivity, or switching field, b, is related to the characteristic size of the device, r, through b = h/(2πqr 2), with q being the unit of electric charge.

Universal quantum computing in linear nearest neighbor architectures

2011 ◽  
Vol 11 (3&4) ◽  
pp. 300-312
Author(s):  
Preethika Kumar ◽  
Steven R. Skinner
Keyword(s):  
Quantum Computing ◽  
Solid State ◽  
Control Parameter ◽  
Nearest Neighbor ◽  
Quantum Computer ◽  
Gate Operation ◽  
One Dimensional ◽  
Single Qubit ◽  
Universal Quantum ◽  
Target Qubit

We introduce a scheme for realizing universal quantum computing in a linear nearest neighbor architecture with fixed couplings. We first show how to realize a controlled-NOT gate operation between two adjacent qubits without having to isolate the two qubits from qubits adjacent to them. The gate operation is implemented by applying two consecutive pulses of equal duration, but varying amplitudes, on the target qubit. Since only a single control parameter is required in implementing our scheme, it is very efficient. We next show how our scheme can be used to realize single qubit rotations and two-qubit controlled-unitary operations. As most proposals for solid state implementations of a quantum computer use a one-dimensional line of qubits, the schemes presented here will be extremely useful.

Determination of rate constants of redox reactions of second order from current-less potential-time curves by a simplified graphical-numerical method

1983 ◽  
Vol 48 (5) ◽  
pp. 1358-1367 ◽  
Author(s):  
Antonín Tockstein ◽  
František Skopal
Keyword(s):  
Numerical Method ◽  
Explicit Form ◽  
Rate Constant ◽  
Optimization Algorithm ◽  
Rate Constants ◽  
Redox Reactions ◽  
Second Order ◽  
Wide Region ◽  
Recurrent Formula

A method for constructing curves is proposed that are linear in a wide region and from whose slopes it is possible to determine the rate constant, if a parameter, θ, is calculated numerically from a rapidly converging recurrent formula or from its explicit form. The values of rate constants and parameter θ thus simply found are compared with those found by an optimization algorithm on a computer; the deviations do not exceed ±10%.

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