Qubits articles from across Nature Portfolio

As many classical neural networks get larger, they can be described as Gaussian processes, the generalization of the normal distribution to infinite dimensions. A similar connection has now been proven for quantum neural networks.

Near-perfect shuttling of silicon spin qubits is demonstrated, closing a gap versus rival systems.

Characterisation of quantum operations is fundamental in quantum technologies - quantum computing in particular - but there’s currently no reliably efficient method to assess mid-circuit measurements, which are a key component for subfields like quantum error correction. Here, the authors fill this gap, integrating MCMs into the framework of randomized benchmarking.

Shallow NV centers in diamond are promising quantum sensors but suffer from reduced coherence times due to surface spin impurities. Here the authors improve coherence times to over 1 ms through interface engineering by oxygen-terminating the diamond surface and patching it with graphene.

Carbon nanotubes are promising hosts for spin qubits, however existing demonstrations show limited coherence times. Here the authors report quantum states in a carbon-nanotube-based circuit driven solely by cavity photons and exhibiting a coherence time of about 1.3 μs.

Cluster states are a key resource in quantum technologies, but generation of large-scale 2D cluster states faces several difficulties. Here, the authors show how to generate a 2 × n ladder-like cluster state via sequential emission of time- and frequency multiplexed photonic qubits from a transmon-based device.

An interconnect based on a low-loss detachable cable connection between two superconducting qubit devices can be used to create elementary quantum networks of interchangeable superconducting quantum devices.

CMOS-based circuits can be integrated with silicon-based spin qubits and can be controlled at milli-kelvin temperatures, which can potentially help scale up these systems.

As many classical neural networks get larger, they can be described as Gaussian processes, the generalization of the normal distribution to infinite dimensions. A similar connection has now been proven for quantum neural networks.

Near-perfect shuttling of silicon spin qubits is demonstrated, closing a gap versus rival systems.

Superconducting qubits could be used to build a fault-tolerant quantum computer. But such a device will require millions of components, and various fundamental challenges remain to be addressed. Success will depend on sustained collaboration between industry and academia.

Controlling qubit–phonon interactions is crucial for solid-state quantum devices. Two recent studies demonstrate that phononic bandgap engineering can alter these interactions, leading to enhanced qubit coherence and scalability.

Large-scale control electronics, operating at cryogenic temperatures, are needed to run practical quantum computers. But scaling such electronics means addressing substantial challenges related to power consumption.

Many important models in theoretical physics — including the standard model of particle physics — are governed by local ‘gauge’ symmetries. Now, a quantum computer has successfully simulated a lattice gauge theory by leveraging this rich symmetry structure.