A research team at Los Alamos National Laboratory is using artificial intelligence to address several critical shortcomings in large-scale malware analysis, making significant advancements in the classification of Microsoft Windows malware and paving the way for enhanced cybersecurity measures. Using their approach, the team set a new world record in classifying malware families.
New research shows that atmospheric pressure fluctuations that pull gases up from underground could be responsible for releasing subsurface methane into Mars’ atmosphere; knowing when and where to look for methane can help the Curiosity rover search for signs of life.
A new, potentially revolutionary artificial intelligence framework called “Blackout Diffusion” generates images from a completely empty picture, meaning that the machine-learning algorithm, unlike other generative diffusion models, does not require initiating a “random seed” to get started.
The elements above iron on the periodic table are thought to be created in cataclysmic explosions like the merger of two neutron stars or in rare classes of supernovae. New research suggests fission may operate in the cosmos during the creation of the heavy elements. Combing through data on a variety of elements that reside in very old stars, researchers have found a potential signature of fission, indicating that nature is likely to produce superheavy nuclei beyond the heaviest elements on the periodic table.
Two labs within Los Alamos National Laboratory have earned recognition for their sustainability-conscious culture: the Chain Lab in Genomics and Bioanalytics and the Center for Integrated Nanotechnologies (CINT).
Recognizing the challenges of running sophisticated applications including complex simulations, data analytics, artificial intelligence and heterogenous workflows at scale in hybrid computing environments, multiple institutions are forming an open-source community -- OCHAMI -- to develop and support a framework for better systems management.
On various sets around New Mexico in 2022, Los Alamos National Laboratory employees talked science and bumped fists with celebrities.
A machine-learning algorithm demonstrated the capability to process data that exceeds a computer’s available memory by identifying a massive data set’s key features and dividing them into manageable batches that don’t choke computer hardware. Developed at Los Alamos National Laboratory, the algorithm set a world record for factorizing huge data sets during a test run on Oak Ridge National Laboratory’s Summit, the world’s fifth-fastest supercomputer. Equally efficient on laptops and supercomputers, the highly scalable algorithm solves hardware bottlenecks that prevent processing information from data-rich applications in cancer research, satellite imagery, social media networks, national security science and earthquake research, to name just a few.
A potentially game-changing theoretical approach to quantum computing hardware avoids much of the problematic complexity found in current quantum computers. The strategy implements an algorithm in natural quantum interactions to process a variety of real-world problems faster than classical computers or conventional gate-based quantum computers can.
New observations of mud cracks made by the Curiosity Rover show that high-frequency, wet-dry cycling occurred in early Martian surface environments, indicating that the red planet may have once seen seasonal weather patterns or even flash floods.
In a banner year for Los Alamos National Laboratory in the competition for Department of Energy Early Career Research Awards, four scientists nabbed multiyear funding for their projects.
Rising temperatures and changes in precipitation are driving increases to streamflow in areas of high-latitude North America where permafrost dominates the landscape.
New theoretical research proves that machine learning on quantum computers requires far simpler data than previously believed. The finding paves a path to maximizing the usability of today’s noisy, intermediate-scale quantum computers for simulating quantum systems and other tasks better than classical digital computers, while also offering promise for optimizing quantum sensors.
A groundbreaking theoretical proof shows that a technique called overparametrization enhances performance in quantum machine learning for applications that stymie classical computers.
New research published in the journal Geophysical Research Letters showed that the plume emitted by the Hunga Volcano eruption in 2022 created the highest lightning flash rates ever recorded on Earth, more than any storm ever documented.
A team of researchers at Los Alamos National Laboratory recently published the most comprehensive study of global COVID-19 variant transitions, which showed significant diversity in variant spread around the globe related to vaccination rates, number of co-circulating variants and immunity from previous infection.
Research using a quantum computer as the physical platform for quantum experiments has found a way to design and characterize tailor-made magnetic objects using quantum bits, or qubits. That opens up a new approach to develop new materials and robust quantum computing.
A new study corrects an important error in the 3D mathematical space developed by the Nobel Prize–winning physicist Erwin Schrödinger and others and used by scientists and industry for more than 100 years to describe how your eye distinguishes one color from another.
A new conceptual framework for incorporating the way plants use carbon and water, or plant dynamics, into fine-scale computer models of wildland fire provides a critical first step toward improved global fire forecasting.
Seasonal temperature, moisture loss from plants and wind speed are what primarily drive fires that sweep across the same landscape multiple times, a new study reveals. These findings and others could help land managers plan more effective treatments in areas susceptible to fire, particularly in the fire-ravaged wildland-urban interfaces of California.
A new paper by a team at Los Alamos National Laboratory is giving researchers new insight into how countries respond to systemic shocks such as the COVID-19 pandemic.
The standard view of gamma-ray bursts as a signature for different types of dying stars might need a rewrite. Recent astronomical observations, supported by theoretical modeling, reveal a new observational fingerprint of neutron-star mergers, which may shed light on the production of heavy elements throughout the universe.
An artificial-intelligence approach borrowed from natural-language processing — much like language translation and autofill for text on your smart phone — can predict future fault friction and the next failure time with high resolution in laboratory earthquakes,. The technique, applying AI to the fault’s acoustic signals, advances previous work and goes beyond by predicting aspects of the future state of the fault’s physical system.
A new study in New Mexico’s San Juan Basin will boost efforts to identify and reduce methane emissions, a key element of the Global Methane Pledge. The research team found that using multiple methods to measure the ratio of ethane to methane in the ambient air around fossil energy development regions can be used to attribute emissions to specific polluters.
Rising sea levels from melting glaciers and ice sheets pose an increasing threat to coastal communities worldwide. A new analysis of high-resolution satellite observations takes a major step forward in assessing this risk by confirming theoretical predictions and computational models of sea-level changes used to forecast climate-change-driven impacts.
A team at Los Alamos National Laboratory has developed a novel approach for comparing neural networks that looks within the “black box” of artificial intelligence to help researchers understand neural network behavior. Neural networks recognize patterns in datasets; they are used everywhere in society, in applications such as virtual assistants, facial recognition systems and self-driving cars.
Los Alamos National Laboratory is leading a new research consortium funded by the Bipartisan Infrastructure Law to identify and characterize the nation’s hundreds of thousands of undocumented orphaned wells and determine their full environmental impact with a focus on methane emissions, a potent greenhouse gas.
Scientists on NASA’s Perseverance mission made a surprising discovery about the composition of rock in Jezero Crater, one that will help them get a better idea of when water existed on Mars, and ultimately, help them understand if the red planet was ever habitable to microbial life.
Comprehensive data from several seasons of field research in the Alaskan Arctic will address uncertainties in Earth-system and climate-change models about snow cover across the region and its impacts on water and the environment.
Recent research proves that under certain conditions, quantum annealing computers can run algorithms—including the well-known Shor’s algorithm—more quickly than classical computers. In most cases, however, quantum annealing does not provide a speed-up compared to classical computing when time is limited, according to a study in Nature Communications.
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