Article 4KN9Q Researchers Build Transistor-Like Gate For Quantum Information Processing -- With Qudits

Researchers Build Transistor-Like Gate For Quantum Information Processing -- With Qudits

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Arthur T Knackerbracket has found the following story:

Quantum information processing promises to be much faster and more secure than what today's supercomputers can achieve, but doesn't exist yet because its building blocks, qubits, are notoriously unstable.

Purdue University researchers are among the first to build a gate - what could be a quantum version of a transistor, used in today's computers for processing information - with qudits. Whereas qubits can exist only in superpositions of 0 and 1 states, qudits exist in multiple states, such as 0 and 1 and 2. More states mean that more data can be encoded and processed.

The gate would not only be inherently more efficient than qubit gates, but also more stable because the researchers packed the qudits into photons, particles of light that aren't easily disturbed by their environment. The researchers' findings appear in npj Quantum Information.

The gate also creates one of the largest entangled states of quantum particles to date - in this case, photons. Entanglement is a quantum phenomenon that allows measurements on one particle to automatically affect measurements on another particle, bringing the ability to make communication between parties unbreakable or to teleport quantum information from one point to another, for example.

The more entanglement in the so-called Hilbert space - the realm where quantum information processing can take place - the better.

Previous photonic approaches were able to reach 18 qubits encoded in six entangled photons in the Hilbert space. Purdue researchers maximized entanglement with a gate using four qudits - the equivalent of 20 qubits - encoded in only two photons.

[...] Next, the team wants to use the gate in quantum communications tasks such as high-dimensional quantum teleportation as well as for performing quantum algorithms in applications such as quantum machine learning or simulating molecules.

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