Toggle light / dark theme

Get the latest international news and world events from around the world.

Log in for authorized contributors

Non-gaussian States Of Light Unlock Universal Computation With Enhanced Success Probabilities And Optimised Photon Requirements

Non-Gaussian states of light represent a crucial component for advancements in quantum technologies, holding immense potential for universal computation, robust error correction, and highly sensitive sensing, yet creating these states remains a significant challenge. Fumiya Hanamura, Kan Takase, and Hironari Nagayoshi, along with their colleagues, now present a new approach to overcome these hurdles, introducing ‘non-Gaussian control parameters’ that offer a more effective way to measure and optimise the generation of these complex states. This method moves beyond traditional benchmarks, such as stellar rank, by providing a continuous and practical measure of non-Gaussianity, and importantly, dramatically reduces the resources needed for successful state creation. Demonstrations across a range of states, including cat states and GKP states, reveal that this technique cuts required photon detections by a factor of three and boosts preparation probability, paving the way for more feasible and scalable quantum technologies and fault-tolerant computation.


Researchers have developed a new method for generating complex states of light that significantly reduces the resources needed for advanced technologies like quantum computing and sensing, achieving a threefold reduction in required measurements and a substantial increase in success rates across various light states.

Don’t sweat it: New device detects sweat biomarker at minimal perspiration rate

A team at Penn State has developed a novel wearable sensor capable of continuously monitoring low rates of perspiration for the presence of a lactate — a molecule the body uses to break down sugars for energy. This biomarker can indicate oxygen starvation in the body’s tissues, which is a key performance indicator for athletes as well as a potential sign of serious conditions such as sepsis or organ failure.

In groundbreaking study, researchers publish brain map showing how decisions are made

Neuroscientists from 22 labs joined forces in an unprecedented international partnership to produce a landmark achievement: a neural map that shows activity across the entire brain during decision-making.

The data, gathered from 139 mice, encompass activity from more than 600,000 neurons in 279 areas of the brain — about 95% of the brain in a mouse. This map is the first to provide a complete picture of what happens across the brain as a decision is made.

“They have created the largest dataset anyone has ever imagined at this scale,” said Dr. Paul W. Glimcher, chair of the department of neuroscience and physiology and director of the Neuroscience Institute at New York University’s Grossman School of Medicine, of the researchers.

Brain–computer interface control with artificial intelligence copilots

Motor brain–computer interfaces (BCIs) decode neural signals to help people with paralysis move and communicate. Even with important advances in the past two decades, BCIs face a key obstacle to clinical viability: BCI performance should strongly outweigh costs and risks. To significantly increase the BCI performance, we use shared autonomy, where artificial intelligence (AI) copilots collaborate with BCI users to achieve task goals. We demonstrate this AI-BCI in a non-invasive BCI system decoding electroencephalography signals. We first contribute a hybrid adaptive decoding approach using a convolutional neural network and ReFIT-like Kalman filter, enabling healthy users and a participant with paralysis to control computer cursors and robotic arms via decoded electroencephalography signals. We then design two AI copilots to aid BCI users in a cursor control task and a robotic arm pick-and-place task. We demonstrate AI-BCIs that enable a participant with paralysis to achieve 3.9-times-higher performance in target hit rate during cursor control and control a robotic arm to sequentially move random blocks to random locations, a task they could not do without an AI copilot. As AI copilots improve, BCIs designed with shared autonomy may achieve higher performance.

Published September 2025 Nature Machine Intelligence:

Preprint: 2024 Oct 12:2024.10.09. https://pmc.ncbi.nlm.nih.gov/articles/PMC11482823/

Tesla’s EPIC Megapack Keynote (full replay) — “Megablock” Is HERE

Questions to inspire discussion.

Technical Specifications.

📏 Q: What are the physical characteristics of the Megapack 3? A: Megapack 3 features a 28-foot long enclosure that can be shipped globally, with 78% fewer connections in the thermal bay, and incorporates a larger battery module and larger cell leveraging the latest cell technology.

⚡ Q: What is the total usable energy capacity of Megapack 3? A: Tesla’s Megapack 3 is designed for 20 megawatt hours of usable AC energy, providing significant storage capacity for large-scale energy projects.

Installation and Efficiency.

🔧 Q: How does Megapack 3 improve installation efficiency? A: Megapack 3 eliminates above-ground cabling and features 78% fewer connections in the thermal bay, significantly streamlining the installation process and reducing potential points of failure.

BREAKING: Tesla Megablock Revolution | Fast Power, Grid Stability & AI Ready Solutions

Tesla megablock revolution | fast power, grid stability & AI ready solutions.

## Tesla’s Megablock is a revolutionary energy storage solution that enables fast power, grid stability, and scalability to support widespread renewable energy adoption, AI data centers, and energy independence.

## Questions to inspire discussion.

🚀 Q: How quickly can Tesla’s Megablock be deployed? A: Tesla’s Megablock can deliver 1 GWh of power in just 20 days, capable of powering 40,000 homes in less than a month.

⚡ Q: What makes the Megablock’s deployment so efficient? A: The Megablock’s modular, plug-and-play design allows for rapid scalability and deployment, with integrated transformers and switchgear reducing complexity.

Grid Stability and Performance.

Tesla Robotaxi Already a Monster Hit

Questions to inspire discussion.

Autonomous Driving Development.

🔄 Q: What version of the Robotaxi software is Tesla currently working on? A: Tesla’s autonomy team is focused on version 14, which will be merged with the public release for consumer vehicles.

🛣️ Q: How is Tesla approaching the expansion of its Robotaxi service area? A: Tesla is taking a cautious approach, prioritizing data collection and safety over rapid expansion.

👀 Q: Are Tesla’s Robotaxis currently fully autonomous? A: The service is currently supervised by a human driver, with the goal of eventually removing the safety monitor for fully autonomous operation.

Future Plans and Strategies.

White dwarf stars could create surprisingly common long-lived habitable zones

A new study by Manuel Barrientos and colleagues from the University of Oklahoma reveals that between 0.6% and 2.5% of white dwarfs in our solar neighborhood undergo dramatic cooling delays that could extend habitable zones for billions of additional years. The secret lies in an element known as neon-22, which, after carbon and oxygen, is the most abundant element inside white dwarfs.

When white dwarfs contain at least 2.5% neon-22 by mass, they undergo a process called “distillation” as their cores crystallize. The research team discovered this occurs because the solid crystals become depleted in neon-22 compared to the surrounding liquid, making them lighter and causes them to float upward where they melt. This astronomical equivalent of a lava lamp releases enormous amounts of gravitational energy, effectively putting the white dwarf’s cooling on pause for up to 10 billion years.

The neon-22 forms during the star’s lifetime through a well understood process. During the helium burning stage, nitrogen-14 (produced by the CNO cycle) transforms into neon-22. This means stars with higher initial abundances of carbon, nitrogen, and oxygen (collectively called “metallicity”) produce more neon-22 in their white dwarf descendants.

/* */