What are time crystals?
Best insight from top research papers
Time crystals are nonequilibrium many-body phases in which the state of the system dynamically approaches a limit cycle. These phases have been the focus of intensive research, but it is still unclear whether they can host quantum correlations. Mostly classical correlations have been observed so far, suggesting that time crystals are effectively classical high-entropy phases . Photonic Time Crystals (PTCs) are dielectric media with a periodically modulated refractive index. They exhibit momentum bands and bandgaps, where the amplitudes of their eigenmodes can exponentially increase or decrease. PTCs have potential applications in making widely tunable lasers that extract energy from the temporal modulation of the medium . Recent experimental work has observed the emergence of a prethermal time crystalline state at quasi-infinite temperature in a solid-state NMR quantum emulator. This state exhibits period-doubling behavior and long-range correlations, ruling out many-body localization .
Answers from top 5 papers
More filters
| Papers (5) | Insight |
|---|---|
| Time crystals are dielectric media that have a periodically modulated refractive index at time scales of an optical cycle. They conserve momentum but not energy and have momentum bands and bandgaps. | |
| Time crystals are states of matter that break discrete time translation symmetry and can exhibit intriguing and robust properties absent in equilibrium systems. | |
14 Mar 2023 | Time-crystals are nonequilibrium many-body phases in which the state of the system dynamically approaches a limit cycle. |
2 Citations | Time crystals are materials in which the refractive index varies periodically and abruptly in time, exhibiting unusual properties such as momentum bands and gaps for wave amplification. |
| Time-crystals are nonequilibrium many-body phases in which the state of the system dynamically approaches a limit cycle. |
Related Questions
What is time series in statistics?5 answersTime series in statistics refers to a sequence of data points indexed in a discrete-time order, often equally spaced, used to analyze patterns over time. Examples include daily stock prices, monthly temperatures, or yearly animal counts. Time series analysis involves studying these data sequences to extract meaningful statistics, identify trends, assess serial dependence, and evaluate stationarity. Forecasting future values based on past observations is a key aspect of time series analysis, aiming to predict outcomes using historical data patterns. Techniques like plotting moving averages, assessing autocorrelation, and partial autocorrelation are commonly employed to understand and interpret time series data effectively.
What is time dilation?5 answersTime dilation refers to the difference in measured time between two clocks due to either relative motion or variances in gravitational potential. This concept is a fundamental aspect of the theory of relativity, as proposed by Einstein. While classical time dilation is associated with velocity and gravitational effects, quantum corrections introduce additional dimensions to this phenomenon, such as kinematic and gravitational quantum time dilations. The idea of time dilation can be derived from the constant speed of light in absolute space, without the need for multiple time dimensions or ethers as proposed in relativity. Time dilation plays a crucial role in cosmology, linking gravitational effects, celestial mechanics, and kinematics to the evolution of galaxies within the spacetime continuum.
What is time gan?4 answersTimeGAN is a generative model for synthesizing time series data. It is designed to preserve the temporal dynamics and relationships between variables across time in the generated sequences. TimeGAN uses a combination of supervised and unsupervised training in a federated framework, which allows for realistic time series data generation. The framework is based on the work of TimeGAN and Federated GAN (FeGAN). It encourages the network to mimic the structure of the training data using an embedded learning space. The results of TimeGAN are combined at a central server using FeGAN, which improves throughput and data privacy. The learned temporal dynamics are combined through a weighting and sampling scheme. TimeGAN has been shown to produce high-quality synthetic time series data that is comparable to the original data.
What is temporal data?5 answersTemporal data refers to data that changes over time or contains information about the passage of time. It is prevalent in various industries, such as sensor devices capturing continuous data from the physical world. Time series data, a type of temporal data, consists of a collection of observations obtained through repeated measurements over time. Temporal data plays a central role in law enforcement and border control, where the speed of knowledge and action is defined by various actors, sites, and materials. In information systems, temporal data processing is important for recording the history of entities, but handling different time granularities and calendar systems is still a challenge. Temporal data mining is crucial for analyzing time-evolving data in business and network intelligence applications, including trend analysis, sentiment analysis on social media, and network monitoring.
What is time?4 answersTime is a complex and enigmatic concept that has been the subject of philosophical and scientific debates throughout history. Philosophers in the eighteenth century, such as Newton, Leibniz, and Clarke, engaged in controversies about the nature of time and its relation to other fundamental elements. Thomas Mann's novel "The Magic Mountain" raises questions about the relationship between time and motion, and whether time is a function of space or vice versa. In the context of cosmology, time is viewed as a force similar to gravity, created by the deformation of the past, and it plays a crucial role in understanding the nature of the Universe. Sociologists emphasize the pervasive presence of time in social life, as it permeates through all aspects of society and is essential for reflection on social order and change. Despite its frequent use, the concept of time becomes elusive when closely examined, and it is challenging to provide a clear account of what exactly is being measured when we measure time.
What is time series?5 answersA time series is a collection of observations recorded in chronological order at regular intervals of time. It is a special type of sequence data that is commonly used in various fields such as forecasting, econometrics, and data analysis. Time series data can represent a wide range of phenomena, including sales, stock prices, product demand, and economic variables like GDP. The analysis of time series data involves studying the dependence and relationships among observations at different points in time. Various techniques and models, such as autoregressive integrated moving average (ARIMA) and deep learning architectures like SCINet, have been developed to analyze and forecast time series data.