Technical Review

A number of different platforms for spin-based computing have emerged over the past few years, offering energy-efficient computing methods. This Technical Review identifies key metrics that must be evaluated to benchmark their performance.

Event generators are used to simulate and describe hadronic collisions in accelerator experiments, but often struggle to describe data from astroparticle experiments that probe hadronic collisions at extreme energies. This Review highlights the complementarity between accelerator and astroparticle experiments that can be exploited, to gain new insights into the nature of hadronic collisions and increase model accuracy across both domains.

This Technical Review highlights advances in cryo-electron microscopy for materials science, covering sample preparation, low-dose imaging and analytical scanning transmission electron microscopy techniques. It discusses strategies to mitigate electron-beam damage and enable high-resolution 2D and 3D imaging of beam-sensitive energy materials.

Tensor networks provide a powerful tool for understanding and improving quantum computing. This Technical Review discusses applications in simulation, circuit synthesis, error correction and mitigation, and quantum machine learning.

Exoplanetary atmosphere studies rely on the quality of laboratory spectroscopy and observational astronomy. This Technical Review highlights the power of high-resolution cross-correlation spectroscopy for advancing the field for all stakeholders.

The renormalization group (RG) is a theoretical framework to transform systems across scales and identify critical points of phase transitions. In recent years, efforts have extended RG to complex networks, which challenge traditional assumptions. This Technical Review covers key approaches and open challenges.

This Technical Review demonstrates how first-principles calculations and effective modelling provide realistic insights into spin–orbit interactions and their engineering in 2D materials and van der Waals heterostructures.

A better understanding of electronic transport in semiconductors is essential for both fundamental and applied physics, as it directly affects key material properties such as the conductivity and thermoelectric quantities. This Technical Review explores different frameworks and computational tools available for computing these properties of semiconductors.

Slow heterogeneous dynamics and the absence of visible structural order make it difficult to numerically and theoretically investigate glass-forming materials. This Technical Review outlines the role that machine learning tools can have and identifies key challenges, possible approaches and appropriate benchmarks.

Nitrogen vacancy centre quantum sensors are quantitative, non-invasive and physically robust probes of condensed matter systems that offer nanoscale resolution across a wide range of temperatures. This Technical Review discusses the connections between NV measurements and important physical characteristics in condensed matter.

Rydberg atoms are sensitive to radio frequency electric fields, which make them useful as sensors. This Technical Review discusses Rydberg sensors that measure the amplitude and phase of electric fields at frequencies from d.c. to THz, as well as technological applications of these sensors.

Ab initio theories of superconductivity allow characterizing and predicting phonon-mediated superconductors. This Technical Review provides an analysis of the different theories, highlighting the main sources of error, either due to inherent approximations or arising from improper practices, and provides a comparison against experimental results.

Understanding vortex pinning in high-temperature superconducting materials is crucial to optimizing their properties. This Technical Review analyses the impact of growth method on vortex microstructure.

Granular matter is ubiquitous in engineering, industrial and natural processes. This Technical Review overviews the latest developments in computational modelling of granular matter with a focus on the role of particle shape and discusses pertaining future challenges.

Graph neural networks have been applied to many important physics tasks at the Large Hadron Collider (LHC). This Technical Review categorizes these applications in a manner accessible to experts and non-experts alike by providing detailed descriptions of LHC physics and graph neural network design considerations.

The dynamic pair distribution function (DyPDF) is an inelastic neutron scattering method that provides information about the local dynamics of a crystalline material. This Technical Review provides a comparison of data across spectrometers and outlines a robust data treatment regimen as a guide to users of this technique.

Photocurrent can be used to reveal the out-of-equilibrium properties of quantum materials over a range of spatiotemporal scales. This Technical Review outlines the principles of photocurrent diagnostics and how it can be used to probe electronic states, quantum geometry and quantum kinetics of materials.

High-resolution images of the local charge distribution in materials often have a key role in establishing structure–property relationships. This Technical Review provides an overview of atomic-resolution charge density imaging techniques in transmission electron microscopy with a focus on recent advances in phase-retrieval methods and applications to heterogeneous materials.

The Dzyaloshinskii–Moriya interaction is an exchange coupling that appears in magnetic systems with spin–orbit coupling. This Technical Review systematically surveys first-principles-calculations methods for DMI in different material systems and for a range of induced magnetic phenomena.

Spin qubits hosted in semiconducting nanostructures controlled and probed electrically are among platforms pursued to serve as quantum computing hardware. This Technical Review surveys experimentally achieved values on coherence, speed, fidelity and multi-qubit array size, reflecting the progress of semiconducting spin qubits over the past two decades.