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]]>- A scalable physical system with well characterized qubits.
- The ability to initialize the states of the qubits to a simple state, such as |000⟩.
- Long relevant coherence times, much longer than the gate operation time.
- A “universal” set of quantum gates.
- A qubit-specific measurement capability.

*A scalable physical system with well characterized qubits.*

*The ability to initialize the states of the qubits to a simple**state, such as |000⟩.*

*Long relevant coherence times, much longer than the gate operation time.*

*A “universal” set of quantum gates.*

*A qubit-specific measurement capability.*

\(|\Psi \rangle = 0.1 |0\rangle + 0.9|1\rangle \)

This function describes the probabilities of the electron being in 0 or 1. In this case there would be 10% chance of a 0 and 90% chance of a 1. The collapse of the wavefunction means that, after a measurement, it will become 1 or 0 depending on which state you measured. A quantum algorithm typically starts by making a full superposition. When you have a lot of qubits, this would mean that you are in all the possible states at the same time (e.g. for 2 qubits, \(|\Psi \rangle = |00\rangle + |01\rangle + |01\rangle + |11\rangle\)). Then some computation is done, which should yield one result. The power of quantum computation is that you can evaluate all the possibilities at the same time. The hard thing is to describe your problem in such a way that you have a high likelihood of measuring the right outcome and a low probability of measuring bad outcomes. Measurements for spin qubits can be done using the Elzerman method. It is quite similar to the initialization. When manipulating your qubits there is a big barrier between the reservoir and the spin qubit (single electron). When an electron is in spin up, it will be able to tunnel out into the reservoir. When this happens, there is for a short while no net charge in the place where the qubit was. After this, a spin down will tunnel back in, as we saw before. Presence or absence of charge is a property we can measure. A charge detector is placed close by the place where the electron can tunnel out. This sensor will give a change in signal whenever you have a spin up. In case of spin down, this charge sensor will not respond since no electron jumps out. Note that this readout method also directly initializes the qubit in spin down. In conclusion, going through these 5 criteria shows that spin qubits have good potential for quantum computation. However, spin qubits are currently not the front runner in the field. That honour belongs to superconducting qubits, which are being pushed hard by IBM and Google. Superconducting qubits are running ahead because they are easier to make, tune and interconnect. The fact that superconducting qubits can be “easily” interconnected, allows for convenient schemes for quantum error correction, which is essential for bigger quantum computers (e.g. >> 10 qubits). But as for spin qubits, the real challenge for superconducting qubits is also the scale up. For superconducting qubits, the control, wiring and cooling of bigger devices becomes much harder, which might make it hard to go beyond a few thousands of qubits. I suspect in the coming year(s), that spin qubits will reach a quality (e.g. fidelity of operation) similar to one demonstrated for the transmons, today. This will be partially due to the availability of better devices (e.g. Intel made) and improvements in the way we do gate operations. In most experimental realisations of spin qubits, the qubits are placed in a row. This is not ideal for large scale operation, as it is not convenient to make two qubits interact at the ends of the spin chain. One of the next big steps for the spin qubit community would be to investigate the feasibility of fabrication and operation of 2D arrays of spin qubits.Stephan is an experimentalist in the Vandersypen group working towards the first logical qubit in silicon. In his free time he is passionate about eating/making food and bouldering.

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]]>Jonas Helsen is an aspiring theorist in the Wehner group where he works on verifying quantum computers. In his free time he enjoys improvisational theater and pretending to be a superhero. He likes the Netherlands but wishes they wouldn’t put peanuts in everything.

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]]>**bringing up the fabrication yield for quantum bits**: Building a ten-qubit chip is harder than building a one-qubit chip. This is especially challenging for nano-scale qubits that run into lithographic limits.**solving the problems of interconnects**: Quantum bits need to be connected to each other as well as to classical control and readout equipment.**managing the heat load of the quantum computer**: Many qubits require very low temperatures at which only limited cooling power is available.**coming up with an architecture**: The growing complexity of the experiments needs to be managed. The level of automation and abstraction needs to increase along with the number of qubits.

16-8-2016 updated version: expanded explanation of the difference between quantum and classical systems and the interaction between classical and quantum components in a computing system

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