Toggle light / dark theme

Whether extra dimensions prove to be physical realities or useful mathematical constructs, they have already transformed our understanding of the universe. They have forced us to reconsider fundamental assumptions about space, time, and the nature of physical law. And they remind us that reality may be far richer and more complex than our everyday experience suggests — that beyond the familiar dimensions of length, width, height, and time, there may exist entire realms waiting to be discovered and, perhaps one day, explored.

The theoretical physicist John Wheeler once remarked that “we live on an island of knowledge surrounded by an ocean of ignorance.” Our exploration of extra dimensions extends the shoreline of that island, pushing into uncharted waters with the tools of mathematics, experiment, and imagination. Though we may never set foot in the fifth dimension or beyond, the very act of reaching toward these hidden aspects of reality expands our perspective and deepens our understanding of the cosmos we call home.

As we continue this grand scientific adventure, we carry forward the legacy of those who first dared to imagine worlds beyond our immediate perception — from the mathematicians who developed the language of higher-dimensional geometry to the physicists who incorporated these concepts into our most fundamental theories. Their vision, coupled with rigorous analysis and experimental testing, illuminates a path toward an ever more complete understanding of the universe in all its dimensions.

The world of robotics is undergoing a significant transformation, driven by rapid advancements in physical AI. This evolution is accelerating the time to market for new robotic solutions, enhancing confidence in their safety capabilities, and contributing to the powering of physical AI in factories and warehouses.

Announced at GTC, Newton is an open-source, extensible physics engine developed by NVIDIA, Google DeepMind, and Disney Research to advance robot learning and development.

NVIDIA Cosmos launched as a world foundation model (WFM) platform under an open model license to accelerate physical AI development of autonomous machines such as autonomous vehicles and robots.

Could we reach Alpha Centauri in just 60 years? The Nuclear Salt Water Rocket (NSWR) might be the answer! With speeds of up to 7.6% of light speed, this game-changing propulsion system could make interstellar travel a reality within a single human lifetime. But how does it work? What challenges stand in the way? In this episode, we break down everything you need to know about NSWR and its potential to revolutionize space travel!
Watch now and explore the future of interstellar exploration!

Paper link : https://path-2.narod.ru/design/base_e… 00:00 Introduction 00:58 How the NSWR Works and Its Breakthrough Potential 03:41 Feasibility and Engineering Challenges 06:30 The Potential Impact on Space Exploration 09:35 Outro 09:44 Enjoy MUSIC TITLE : Starlight Harmonies MUSIC LINK : https://pixabay.com/music/pulses-star… Visit our website for up-to-the-minute updates: www.nasaspacenews.com Follow us Facebook: / nasaspacenews Twitter: / spacenewsnasa Join this channel to get access to these perks: / @nasaspacenewsagency #NSN #NASA #Astronomy#NuclearSaltWaterRocket #SpaceExploration #InterstellarTravel #AlphaCentauri #FutureOfSpaceTravel #SpaceTechnology #RocketScience #FastestRocket #NASA #RobertZubrin #DeepSpaceExploration #SpacePropulsion #NuclearRockets #Physics #Astrophysics #NewSpaceRace #SpaceEngineering #CosmicExploration #BeyondOurSolarSystem #WarpDrive #Science #SpaceScience #RocketTechnology #StarTravel #FusionPropulsion #MarsToStars #LightSpeedTravel #FuturisticTechnology #HighThrustPropulsion #SpaceFrontier #NextGenSpacecraft.

Chapters:
00:00 Introduction.
00:58 How the NSWR Works and Its Breakthrough Potential.
03:41 Feasibility and Engineering Challenges.
06:30 The Potential Impact on Space Exploration.
09:35 Outro.
09:44 Enjoy.

MUSIC TITLE : Starlight Harmonies.

MUSIC LINK : https://pixabay.com/music/pulses-star

Visit our website for up-to-the-minute updates:

Physicists at TU Dortmund University have periodically driven a time crystal and discovered a remarkable variety of nonlinear dynamic phenomena, ranging from perfect synchronization to chaotic behavior within a single semiconductor structure. The team has now published its latest findings in the journal Nature Communications.

For their current research, Dr. Alex Greilich’s team from the Department of Physics utilized a highly robust time crystal, previously introduced in Nature Physics last year. The crystal, made of , was continuously illuminated with a laser during the initial experiment. This interaction caused a nuclear spin polarization, which in turn spontaneously generated oscillations, embodying the essence of a time crystal through periodic behavior under constant excitation.

In the newly published follow-up study, the team explored the dynamic phases of the time crystal. They illuminated the semiconductor periodically instead of continuously, while also varying the frequency of the periodic drive. The observed behavior of the time crystal, its , ranged from perfect to chaotic dynamics.

A new paper explains how signals oscillating at complex-valued frequencies could transform sensing, imaging, and communication technologies. Researchers from the Advanced Science Research Center at the CUNY Graduate Center (CUNY ASRC) and Florida International University have published new findin

Heaviside was born in Camden Town, London, at 55 Kings Street [ 3 ] : 13 (now Plender Street), the youngest of three children of Thomas, a draughtsman and wood engraver, and Rachel Elizabeth (née West). He was a short and red-headed child, and suffered from scarlet fever when young, which left him with a hearing impairment. A small legacy enabled the family to move to a better part of Camden when he was thirteen and he was sent to Camden House Grammar School. He was a good student, placing fifth out of five hundred students in 1865, but his parents could not keep him at school after he was 16, so he continued studying for a year by himself and had no further formal education. [ 4 ] : 51

Heaviside’s uncle by marriage was Sir Charles Wheatstone (1802–1875), an internationally celebrated expert in telegraphy and electromagnetism, and the original co-inventor of the first commercially successful telegraph in the mid-1830s. Wheatstone took a strong interest in his nephew’s education [ 5 ] and in 1867 sent him north to work with his older brother Arthur Wheatstone, who was managing one of Charles’ telegraph companies in Newcastle-upon-Tyne. [ 4 ] : 53

Two years later he took a job as a telegraph operator with the Danish Great Northern Telegraph Company laying a cable from Newcastle to Denmark using British contractors. He soon became an electrician. Heaviside continued to study while working, and by the age of 22 he published an article in the prestigious Philosophical Magazine on ‘The Best Arrangement of Wheatstone’s Bridge for measuring a Given Resistance with a Given Galvanometer and Battery’ [ 6 ] which received positive comments from physicists who had unsuccessfully tried to solve this algebraic problem, including Sir William Thomson, to whom he gave a copy of the paper, and James Clerk Maxwell. When he published an article on the duplex method of using a telegraph cable, [ 7 ] he poked fun at R. S. Culley, the engineer in chief of the Post Office telegraph system, who had been dismissing duplex as impractical.

Network models provide a flexible way of representing objects and their multifaceted relationships. Deriving a network entails mapping hidden structures in inevitably noisy data—a critical task known as reconstruction. Now Gang Yan and Jia-Jie Qin of Tongji University in China have provided a mathematical proof showing what makes some networks easier to reconstruct than others [1].

Complex systems in biology, physics, and social sciences tend to involve a vast number of interacting entities. In a network model, these entities are represented by nodes, linked by connections weighted to describe the strength of each interaction. Yan and Qin took an empirical dataset and used a statistical inference method to calculate the likelihood that any pair of nodes is directly linked. Then, based on the true positive and false positive rates of these inferred connections, they analyzed the fidelity of the reconstructed networks. They found that the most faithful reconstructions are obtained with systems for which the number of connections per node varies most widely across the network. Yan and Qin saw the same tendency when they tested their model on synthetic and real networks, including metabolic networks, plant-pollinator webs, and power grids.

With the rapid increase in available data across research areas, network reconstruction has become an important tool for studying complex systems. Yan and Qin say their new result both solves the problem of what complex systems can be easily mapped into a network and provides a solid foundation for developing methods of doing so.

A team of physicists uncovered a strange twist in how superconductors behave when they’re reduced to just a few atomic layers. Using powerful magnetic imaging, they found that superconductivity in ultra-thin materials doesn’t follow the usual rules – it becomes surface-based rather than distribut

Foie gras—the fattened liver of ducks or geese—is a French delicacy prized for its rich, buttery flavor. But its production, which involves force-feeding the animals, has led to bans in several countries.

Now, a team of scientists says they’ve developed a more ethical alternative: one that mimics the taste and texture of the dish, minus the controversy.

The results were published Tuesday in the journal Physics of Fluids.

Researchers at Osaka University have revealed a link between the equations describing strain caused by atomic dislocations in crystalline materials and a well-established formula from electromagnetism, an insight that could advance research in condensed matter physics. A fundamental goal of physi