Dec 19, 2022
Mercury’s superconductivity explained at long last
Posted by Shubham Ghosh Roy in category: space
More than 100 years ago, the physicist Heike Kamerlingh Onnes discovered that solid mercury acts as.
More than 100 years ago, the physicist Heike Kamerlingh Onnes discovered that solid mercury acts as.
You can now create high resolution 3D mesh models from text in just minutes using Magic3D, an amazing new AI!
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Two planets that astronomers discovered on the Kepler mission may not be the rocky, Earth-like bodies that we originally believed. Instead, a new study suggests that they could be two water worlds, and that they are less dense than astronomers originally posited. What’s intriguing about these worlds is that they are believed to be somewhat similar to Europa, which is a rocky core encased in water and capped in ice.
The past and the future are tightly linked in conventional quantum mechanics. Perhaps too tightly. A tweak to the theory could let quantum possibilities increase as space expands.
Danuri, South Korea’s first deep-space exploration mission, is finally arriving at the moon after a four-month voyage.
The Danuri spacecraft was expected to begin entering lunar orbit at on Friday (Dec. 17) at 2:45 p.m. EST (1945 GMT, 2:45 a.m. Dec. 17 in South Korea), according to a statement (opens in new tab) from the Korea Aerospace Research Institute (KARI). The maneuver, the first of five planned engine burns through Dec. 28 to refine Danuri’s orbit around the moon, will clear the way for the probe to get started on its lunar science objectives.
So far the mission has produced information on Io, Ganymede and Europa.
NASA’s Juno mission already brought us much data on the moons Ganymede and Europa. Now, according to a press release by the agency published on Wednesday, the spacecraft is exploring one more of Jupiter’s moons: Io. Io is notably the most volcanic place in the solar system.
Continue reading “NASA’s Juno collects key data on Jupiter’s moons” »
Both animals and people use high-dimensional inputs (like eyesight) to accomplish various shifting survival-related objectives. A crucial aspect of this is learning via mistakes. A brute-force approach to trial and error by performing every action for every potential goal is intractable even in the smallest contexts. Memory-based methods for compositional thinking are motivated by the difficulty of this search. These processes include, for instance, the ability to: recall pertinent portions of prior experience; (ii) reassemble them into new counterfactual plans, and (iii) carry out such plans as part of a focused search strategy. Compared to equally sampling every action, such techniques for recycling prior successful behavior can considerably speed up trial-and-error. This is because the intrinsic compositional structure of real-world objectives and the similarity of the physical laws that control real-world settings allow the same behavior (i.e., sequence of actions) to remain valid for many purposes and situations. What guiding principles enable memory processes to retain and reassemble experience fragments? This debate is strongly connected to the idea of dynamic programming (DP), which using the principle of optimality significantly lowers the computing cost of trial-and-error. This idea may be expressed informally as considering new, complicated issues as a recomposition of previously solved, smaller subproblems.
This viewpoint has recently been used to create hierarchical reinforcement learning (RL) algorithms for goal-achieving tasks. These techniques develop edges between states in a planning graph using a distance regression model, compute the shortest pathways across it using DP-based graph search, and then use a learning-based local policy to follow the shortest paths. Their essay advances this field of study. The following is a summary of their contributions: They provide a strategy for long-term planning that acts directly on high-dimensional sensory data that an agent may see on its own (e.g., images from an onboard camera). Their solution blends traditional sampling-based planning algorithms with learning-based perceptual representations to recover and reassemble previously recorded state transitions in a replay buffer.
The two-step method makes this possible. To determine how many timesteps it takes for an optimum policy to move from one state to the next, they first learn a latent space where the distance between two states is the measure. They know contrastive representations using goal-conditioned Q-values acquired through offline hindsight relabeling. To establish neighborhood criteria across states, the second threshold this developed latent distance metric. They go on to design sampling-based planning algorithms that scan the replay buffer for trajectory segments—previously recorded successions of transitions—whose ends are adjacent states.
Title: Discovery and properties of the earliest galaxies with confirmed distances
Authors: * B. E. Robertson, *S. Tacchella, B. D. Johnson, K. Hainline, L. Whitler, D. J. Eisenstein, R. Endsley, M. Rieke, D. P. Stark, S. Alberts, A. Dressler, E. Egami, R. Hausen, G. Rieke, I. Shivaei, C. C. Williams, C. N. A. Willmer, S. Arribas, N. Bonaventura, A. Bunker, A. J. Cameron, S. Carniani, S. Charlot, J. Chevallard, M. Curti, E. Curtis-Lake, F. D’Eugenio, P. Jakobsen, T. J. Looser, N. Lützgendorf, R. Maiolino, M. V. Maseda, T. Rawle, H.-W. Rix, R. Smit, H. Übler, C. Willott, J. Witstok, S. Baum, R. Bhatawdekar, K. Boyett, Z. Chen, A. de Graaff, M. Florian, J. M. Helton, R. E. Hviding, Z. Ji, N. Kumari, J. Lyu, E. Nelson, L. Sandles, A. Saxena, K. A. Suess, F. Sun, M. Topping, I. E. B. Wallace (* equal contribution)
First Author’s Institution: University of California, Santa Cruz.
Scientists determine that a gamma-ray burst detected on Earth was caused by a space explosion that happened less than 900 million years ago.
On September 5, 2021, light from a very energetic gamma-ray burst (GRB) – an incredibly energetic explosion that happened in a faraway galaxy – reached our planet. To get to Earth, it traveled for more than 12.8 billion years. The glow began its journey when the Universe (which is considered to be 13.7 billion years old) was just 880 million years old.
A worldwide team of astronomers proceeded to study the explosion’s afterglow in the months that followed this finding in order to understand what caused it. Dr. Andrea Rossi, a researcher at the Italian National Institute of Astrophysics (INAF), headed the group. Professor Carole Mundell from the University of Bath was also involved.
Scientists have failed to detect a key signal from space – and used it to explain some of the earliest parts of the universe.
The inability to pick up the signal has allowed researchers to better understand the first galaxies to exist. It is one of the first times they have been able to study the period known as the “cosmic dawn”, when the first stars and galaxies came into being.
Scientists are now able to place limits on the mass and energy coming out of those first stars and galaxies – using a counterintuitive method.