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Category: physics – Page 72

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Hyperjumps, wormholes, and warp drives sound like science fiction, but they’re actually based on real science! Though I believe out of the three, warp drives are the most plausible. The math seems to agree. Today I want to tell you about a new way of analysing and visualizing warp drives.

Code: https://github.com/pbbp0904/WarpFactory.

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#science #sciencenews #warpdrives #physics

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Last September, the James Webb Space Telescope, or JWST, discovered JWST-ER1g, a massive ancient galaxy that formed when the universe was just a quarter of its current age. Surprisingly, an Einstein ring is associated with this galaxy. That’s because JWST-ER1g acts as a lens and bends light from a distant source, which then appears as a ring—a phenomenon called strong gravitational lensing, predicted in Einstein’s theory of general relativity.

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Astronomers have produced the largest 3D map of the universe, which can be explored in an interactive VR video. In the process, they’ve uncovered some tantalizing hints that our understanding of physics, including the ultimate fate of the cosmos, could be wrong.

The Dark Energy Spectroscopic Instrument (DESI) is a huge international project to map out the universe in three dimensions, which began collecting data in 2021. This early version of the map only includes data collected during the first year – 5.7 million galaxies and quasars out of the planned goal of 40 million. This data allows the scientists to peer as far as 11 billion light-years into deep space and time, providing a glimpse into the very early universe with an unprecedented precision of less than 1%.

With a view that zoomed-out, the cosmos resembles a colossal web, made up of bright strands of galaxies separated by unimaginably empty voids. If you feel up for an existential crisis, check out this VR fly-through video and remember that each of these blurry blobs of light is an entire galaxy, each containing millions of stars and billions of planets.

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The laws of nature or physics are assumed to be everywhere the same, on the far side of the universe as sure as on the far side of your house. Otherwise science itself could not succeed. But are these laws equally constant across time? Might the deep laws of physics change over eons of time? The implications would be profound.

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Lee Smolin is a theoretical physicist, a researcher at the Perimeter Institute for Theoretical Physics, and an adjunct professor of physics at the University of Waterloo.

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Fast radio bursts (FRBs) represent the most intense radio explosions in the universe. Since the first discovery in 2007, FRBs have garnered significant attention, culminating in the 2023 Shaw Prize in Astronomy. With yet unknown origin, these extreme cosmic bursts are among the most enigmatic phenomena in astronomy as well as physics.

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Do you know what they’ve discovered? This is the proton engine that Einstein predicted decades ago and that, for the first time, they’ve managed to materialize. The best part? It challenges even the laws of physics and the universe, and it’s going to decarbonize transportation.

Nuclear fusion has long been a sought-after but elusive goal for science. It involves joining atomic nuclei to release energy, the same process that occurs in the Sun and other stars. In fact, it’s a process similar to what we saw two weeks ago with the plasma engine.

Unlike nuclear fission used in current nuclear power plants—which, remember, we are highly critical of due to its lack of being an eco-friendly or renewable option—fusion offers the promise of a virtually inexhaustible and clean energy source.

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Can you wirelessly power wireless devices, thus improving and advancing the technology known an “Internet of Things” (IoT)? This is what a recent study published in Energy & Environmental Science hopes to address as a team of researchers from the University of Utah investigated how pyroelectrochemical cell (PECs) could be used to self-charge IoT devices through changes in immediate surrounding temperature, also known as ambient temperature. This study holds the potential to help a myriad of industries, including agriculture and machinery, by allowing IoT devices to charge without the need for electrical outlets.

“We’re talking very low levels of energy harvesting, but the ability to have sensors that can be distributed and not need to be recharged in the field is the main advantage,” said Dr. Roseanne Warren, who is an associate professor in the Mechanical Engineering Department at the University of Utah and a co-author on the study. “We explored the basic physics of it and found that it could generate a charge with an increase in temperature or a decrease in temperature.”

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In a revolutionary scientific endeavor, researchers are using 5,000 miniature robots perched atop a mountaintop telescope to peer an astonishing 11 billion years into the past. This cutting-edge instrument, known as the Dark Energy Spectroscopic Instrument (DESI), is capturing light from distant objects in space, allowing scientists from the Lawrence Berkeley National Laboratory to map our cosmos as it was in its infancy and trace its evolution to the present day.

Why is this so important? Understanding how our universe has evolved is intrinsically linked to predicting its ultimate fate and unraveling one of the biggest mysteries in physics: dark energy. This enigmatic force is causing our universe to expand at an ever-increasing rate, and DESI is providing us with unprecedented insights into its effects over the past 11 billion years.

DESI has created the largest and most precise 3D map of our cosmos ever constructed, enabling scientists to measure the expansion history of the young universe with a precision better than 1 percent for the first time. This unparalleled view of the universe’s evolution is shedding light on the interplay between matter, dark matter, and dark energy in shaping the cosmos.

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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.

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