Menu

Blog

Archive for the ‘space’ category: Page 157

Dec 19, 2022

A 107-year-old Einstein theory about how the universe began, Which is 100% correct

Posted by in category: space

Read more about A 107-year-old Einstein theory about how the universe began, Which is 100% correct.

Dec 19, 2022

Perturbation theory of large scale structure in the $ LambdaCDM Universe: Exact time evolution and the two-loop power spectrum

Posted by in categories: energy, space

The large-scale structure (LSS) of the Universe is obviously nonlinear and very complicated. However, the scale of onset of nonlinearity is well separated from the size of the Universe which makes a large portion of the structure formation modes accessible to perturbation theory (PT). The latter is itself complicated by the time dependence of the lambdaCDM background. The authors provide an exact all-order recursive solution for the PT kernels, which allows them to go beyond the Einstein-de Sitter approximation for the time dependence, and quantify the deviation at the two-loop level in the 10% range, a deviation detectible with upcoming observations.

Dec 19, 2022

Space Renaissance Christmas Special 2022

Posted by in categories: law, space, sustainability

The last event of 2022 will take place December 19th: Christmas Special meeting. with our president Prof. Bernard Foing!
We’ll have a look at what we have done in 2022, and we’ll announce the program of 2023.
The Zoom meeting will be open to all of the SRI Members and invited friends – just registered or going to register during the meeting.
All the participants will have the possibility to make questions to the SRI President, the Founder and the Board of Directors, about the 2023 program. Criticisms and proposals will be welcome too.
We have a huge programme for 2023, and we are going through some key steps, to achieve an higher legal status for our association: to be registered as a not for profit entity on the Unic National Register of the Third Sector Entities (RUNTS). Such an achievement will allow SRI to call Italian taxpayers to target the 5×1000 of their yearly tax to SRI, and the donations to be deducted from the tax declaration. These conditions, when achieved, will greatly contribute to the sustainability of our initiatives.
We are asking each of the SRI members and supporters to assume this priority for December 2022: to bring onboard many new members and to seek for donors and sponsors!
We will celebrate together during the Xmas Special event and exchange season greetings and wishes for a vibrant year 2023 for Space Renaissance International!

Dec 19, 2022

Mercury’s superconductivity explained at long last

Posted by in category: space

More than 100 years ago, the physicist Heike Kamerlingh Onnes discovered that solid mercury acts as.

Dec 18, 2022

NVIDIA’s Revolutionary AI CREATES Text to 3D models in minutes!

Posted by in categories: robotics/AI, space

You can now create high resolution 3D mesh models from text in just minutes using Magic3D, an amazing new AI!

Follow Me or AI will not be your friend!

Continue reading “NVIDIA’s Revolutionary AI CREATES Text to 3D models in minutes!” »

Dec 18, 2022

Scientists may have discovered two water worlds

Posted by in category: space

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.

Dec 18, 2022

Physicists Rewrite a Quantum Rule That Clashes With Our Universe

Posted by in categories: quantum physics, space

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.

Dec 17, 2022

South Korea’s 1st moon probe Danuri begins to enter lunar orbit

Posted by in category: space

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.

Dec 17, 2022

NASA’s Juno collects key data on Jupiter’s moons

Posted by in category: space

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” »

Dec 17, 2022

This AI Paper Introduces a General-Purpose Planning Algorithm called PALMER that Combines Classical Sampling-based Planning Algorithms with Learning-based Perceptual Representations

Posted by in categories: information science, policy, robotics/AI, space, sustainability

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.