An international team of engineers and physicists have found a way to use quantum light to improve the performance of cutting-edge spectroscopy.
Their new technique enables measurements of infrared electric fields which are twice as sensitive as previous developments in a process called time-domain spectroscopy.
The researchers say their work could help open up new applications in security and medical diagnostics.
For the first time, a team of researchers at Lawrence Livermore National Laboratory (LLNL) quantified and rigorously studied the effect of metal strength on accurately modeling coupled metal/high explosive (HE) experiments, shedding light on an elusive variable in an important model for national security and defense applications.
The team used a Bayesian approach to quantify metal strength uncertainty with tantalum and two common explosive materials and integrated it into a coupled metal/HE model. Their findings could lead to more accurate models for equation-of-state-studies, which assess the state of matter a material exists in under different conditions. Their paper —featured as an editor’s pick in the Journal of Applied Physics —also suggested that metal strength uncertainty may have an insignificant effect on result.
“There has been a long-standing field lore that HE model calibrations are sensitive to the metal strength,” said Matt Nelms, the paper’s first author and a group leader in LLNL’s Computational Engineering Division (CED). “By using a rigorous Bayesian approach, we found that this is not the case, at least when using tantalum.”
Google’s February 2025 update patches 47 Android flaws, including CVE-2024–53104, exploited in the wild, and CVE-2024–45569 in Qualcomm WLAN.
PyPI introduces a project archival feature to improve supply chain security, with archived projects remaining installable but unmaintained.
WASHINGTON — As the demand for digital security grows, researchers have developed a new optical system that uses holograms to encode information, creating a level of encryption that traditional methods cannot penetrate. This advance could pave the way for more secure communication channels, helping to protect sensitive data.
“From rapidly evolving digital currencies to governance, healthcare, communications and social networks, the demand for robust protection systems to combat digital fraud continues to grow,” said research team leader Stelios Tzortzakis from the Institute of Electronic Structure and Laser, Foundation for Research and Technology Hellas and the University of Crete, both in Greece.
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PLUS: MGM settles breach suits; AWS doesn’t trust you with security defaults; A new. NET backdoor; and more.
As the demand for digital security grows, researchers have developed a new optical system that uses holograms to encode information, creating a level of encryption that traditional methods cannot penetrate. This advance could pave the way for more secure communication channels, helping to protect sensitive data.
“From rapidly evolving digital currencies to governance, health care, communications and social networks, the demand for robust protection systems to combat digital fraud continues to grow,” said research team leader Stelios Tzortzakis from the Institute of Electronic Structure and Laser, Foundation for Research and Technology Hellas and the University of Crete, both in Greece.
“Our new system achieves an exceptional level of encryption by utilizing a neural network to generate the decryption key, which can only be created by the owner of the encryption system.”
In today’s AI news, ElevenLabs said on Thursday it has raised $180 million in a new funding round that triples the voice cloning artificial intelligence startup’s valuation to $3.3 billion. The Series C funding round was co-led by Andreessen Horowitz and Iconiq Growth, with participation from additional new investors.
On Thursday, OpenAI announced that it is deepening its ties with the US government through a partnership with the National Laboratories and expects to use AI to “supercharge” research across a wide range of fields to better serve the public.
“This is the beginning of a new era, where AI will advance science, strengthen national security, and support US government initiatives,” OpenAI said.
In other advancements, Cerebras Systems announced today it will host DeepSeek’s breakthrough R1 artificial intelligence model on U.S. servers, promising speeds up to 57 times faster than GPU-based solutions while keeping sensitive data within American borders. The move comes amid growing concerns about China’s rapid AI advancement and data privacy.
And, the US Copyright Office issued AI guidance this week that declared no laws need to be clarified when it comes to protecting authorship rights of humans producing AI-assisted works. “Questions of copyrightability and AI can be resolved pursuant to existing law, without the need for legislative change,” the Copyright Office said.
BIG Projects To Solve Pressing Issues In Science — Dr. Christopher Stubbs, Ph.D. — Professor of Physics and Astronomy, Harvard University.
Dr. Christopher Stubbs, Ph.D. is the Samuel C. Moncher Professor of Physics and Astronomy, and has recently served as the Dean of Science in the Faculty of Arts and Sciences, at Harvard University (https://astronomy.fas.harvard.edu/peo…
Dr. Stubbs is an experimental physicist working at the interface between particle physics, cosmology and gravitation. His interests include experimental tests of the foundations of gravitational physics, searches for dark matter, characterizing the dark energy, and observational cosmology.
The world of AI is evolving at a breakneck pace with new models constantly being created. With so much rapid innovation, it is essential to have the flexibility to quickly adapt applications to the latest models. This is where Azure Container Apps serverless GPUs come in.
Azure Container Apps is a managed serverless container platform that enables you to deploy and run containerized applications while reducing infrastructure management and saving costs.
With serverless GPU support, you get the flexibility to bring any containerized workload, including new language models, and deploy them to a platform that automatically scales with your customer demand. In addition, you get optimized cold start, per-second billing and reduced operational overhead to allow you to focus on the core components of your applications when using GPUs. All the while, you can run your AI applications alongside your non-AI apps on the same platform, within the same environment, which shares networking, observability, and security capabilities.
