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Entropy is central to statistical physics, but it has multiple meanings. This Review clarifies the strengths of each use and the connections between them, seeking to bolster crosstalk between researchers and to emphasize the power of inference for non-equilibrium physics.
Dipolar many-body systems provide a promising platform to study quantum phases and exotic phenomena such as dipolar liquids, dipolar solids and superfluids. This Review discusses dipolar many-body complexes and their interactions in 2D stacked transition metal dichalcogenide heterobilayers and offers insights into the unique properties of various exciton species.
This Perspective argues that the development of 99Mo production methods complementary to reactor-based methodology is strategic in the short-to-medium term. Localized and resilient 99Mo production routes might guarantee access to important diagnostic procedures even in the case of unpredictable global events.
In the 1980s, the discovery of electron states that fractionalize in the presence of a time-reversal symmetry breaking magnetic field opened up new directions in condensed matter physics. In 2023, evidence has accumulated that a version of these states in which the time-reversal symmetry breaking is spontaneous appears in moiré materials.
Quantum sensing exploits properties of quantum systems to go beyond what is possible with traditional measurement techniques, hence opening exciting opportunities in both low-energy and high-energy particle physics experiments.
This Review covers the intriguing physics behind orbital angular momentum lasers, summarizing the exciting prospects at the interface between structured light and structured matter.
Non-fullerene acceptors have boosted the development of organic photovoltaics. This Review highlights the photophysics and device physics of non-fullerene organic photovoltaics, including exciton generation, diffusion, transport, separation and charge recombination.
Machine learning techniques may appear ill-suited for application in fields that prioritize rigor and deep understanding; however, they have recently found unexpected uses in theoretical physics and pure mathematics. In this Perspective, Gukov, Halverson and Ruehle have discussed rigorous applications of machine learning to theoretical physics and pure mathematics.
Neural operators learn mappings between functions on continuous domains, such as spatiotemporal processes and partial differential equations, offering a fast, data-driven surrogate model solution for otherwise intractable numerical simulations of complex real-world problems.
Developing photodetectors that work across the electromagnetic spectrum remains a challenge, and there are many trade-offs to be considered, including speed, efficiency, noise, spectral detection range and cost. This Review discusses the photophysical attributes of the active materials that define the interrelated aspects of response amplitude and temporal dynamics in photodetectors.
This Review summarizes differences in several mechanical properties that play a role in human cancer development, at the cell and tissue levels. Comprehensive cell and tissue quantitative mechanical properties are provided based on cancer types and organs of origin.
The standard model of particle physics describes the fundamental constituents of matter and their interactions. We review the status of experimental hints for new physics, which, if confirmed, would require the extension of the standard model with new particles and new interactions.
Similar to acoustic and electromagnetic waves, water waves are classical waves that can be controlled by artificial structures such as water wave crystals and metamaterials. This Review surveys the development of water wave manipulation using artificial structures and describes its potential applications.
In 2023, pulsar timing arrays announced what could become the first ever discovery of a stochastic gravitational wave background: the random superposition of gravitational waves permeating the cosmos — a vestige of cosmic processes in the Universe.
Structure and function of biological tissues are closely intertwined. This Review surveys the challenges in uncovering critical physical elements involved in the mechanical regulation of curved tissues across different length scales and examines how changes in curvature influence cell functions.
In 2023, a number of experiments on trilayer 2D structures uncovered new exciton states that have an electrically-tunable dipole moment and show a quantum many-body phase diagram.
Despite recent breakthroughs in quantum error correction experiments with trapped ions, superconducting circuits and reconfigurable atom arrays, there are still several technological challenges to overcome.
Generative machine learning models seek to approximate and then sample the probability distribution of the data sets on which they are trained. This Perspective article connects these methods to historical studies of information processing and attractor geometry in nonlinear systems.
Understanding the W boson as accurately as possible, including knowing its mass, has been a priority in particle physics for decades. This Perspective article gives an overview of the role of the W boson mass in the Standard Model and its extensions and compares techniques for measuring it.