Parameter estimation with gravitational waves
Nelson Christensen and Renate Meyer
Rev. Mod. Phys. 94, 025001 (2022) – Published 8 April 2022

Following their first detection, gravitational wave signals from astrophysical binary mergers have been collected by the LIGO-Virgo network of interferometers, inaugurating the era of gravitational wave astronomy. With a new generation of instruments, one major challenge is the development of statistical and computational methods for estimating the physical parameters that characterize the emitting systems and the source populations. This review presents the Bayesian inference techniques used for parameter estimation from gravitational wave observations by ground-based interferometers. The application of such methods to the signals observed by LIGO-Virgo is illustrated with results in fundamental physics, astrophysics, and cosmology.

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Interfacial thermal resistance: Past, present, and future
Jie Chen, Xiangfan Xu, Jun Zhou, and Baowen Li
Rev. Mod. Phys. 94, 025002 (2022) – Published 22 April 2022

As devices and circuits scale to ever smaller sizes and thermal management in them becomes more important, heat transport across their interfaces plays a crucial role in their development. While the study of interfacial thermal resistance goes back almost 90 years, its increasing importance has led to significant recent progress in theory, experiment, and simulation. This review chronicles this progress for solid-solid, solid-liquid, and solid-gas interfaces, discusses how to tailor interfaces to minimize the resistance, and mentions some of the remaining challenges.

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Coupling of mechanical deformation and electromagnetic fields in biological cells
Mehdi Torbati, Kosar Mozaffari, Liping Liu, and Pradeep Sharma
Rev. Mod. Phys. 94, 025003 (2022) – Published 6 May 2022

A distinctive characteristic of the biological cell is its ability to mechanically deform to crawl or squeeze through trapped spaces. When a cell is taken apart, the structural deformation of its cellular components as biological matter can be manipulated by electrical and magnetic fields. Their response to the external fields opens an opportunity for biomedical intervention of controlling the movement of a cell. The understanding of the coupling between the mechanical deformation and the nonlinear electromagnetic behavior, however, requires the formulation of electrostatics and continuum mechanics in elastic material. This review reports on several major advances in elucidating the physics of biological matter and surveys new challenges pertinent to cellular biomechanics.

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Spoof surface plasmon photonics
Francisco J. Garcia-Vidal, Antonio I. Fernández-Domínguez, Luis Martin-Moreno, Hao Chi Zhang, Wenxuan Tang, Ruwen Peng, and Tie Jun Cui
Rev. Mod. Phys. 94, 025004 (2022) – Published 20 May 2022

Structuring metallic surfaces allows for the support of surface electromagnetic modes at frequencies for which they would not be allowed for smooth surfaces. These modes are called “spoof surface plasmons” because of their similarity to surface plasmons that are supported at optical frequencies for smooth surfaces. This article describes the physics that underlies the behavior of spoof surface plasmons and how these modes are used in applications that require the manipulation of electromagnetic fields at frequencies below optical.

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Tensor lattice field theory for renormalization and quantum computing
Yannick Meurice, Ryo Sakai, and Judah Unmuth-Yockey
Rev. Mod. Phys. 94, 025005 (2022) – Published 26 May 2022

One goal in understanding quantum chromodynamics (QCD) includes solving how quarks and gluons combine to form the hadrons and nuclei seen in nature. With lattice QCD, progress has been made regarding the calculation of masses and couplings. However, the real-time evolution and the critical behavior at finite density of strong particles in colliders, stars, or after the big bang remain a challenging problem despite their potential to detect the existence of new physics. The tensor methods for lattice field theories provide a route to handle strongly correlated systems across different subfields using renormalization group methods or quantum computing.

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