Largest Universe Simulation EVER

The world’s largest simulation of the cosmos lays a new computational foundation for simultaneous extreme-scale dark matter and astrophysical investigations.

Researchers used the Frontier supercomputer to conduct the largest astrophysical simulation to date, simulating both atomic and dark matter across universe-sized scales. This was facilitated by advancements in HACC, a code developed to run on exascale-class supercomputers, now capable of performing quintillion calculations per second. 

This breakthrough in cosmological hydrodynamics simulations will aid in matching observational data with theoretical models.

Universe Simulation Breakthrough

The universe just expanded—at least in the realm of computer simulations.

Earlier this month, researchers at the Department of Energy’s Argonne National Laboratory harnessed the power of the world’s fastest supercomputer to execute the largest astrophysical simulation of the universe ever achieved.   READ MORE...

Einstein Vindicated

Albert Einstein’s prediction about how gravity behaves has been tested on a cosmic scale. Albert Einstein’s prediction about how gravity behaves has been supported by an international team of researchers who studied how the force acts on cosmic scales.

Dark Energy Spectroscopic Instrument (DESI) researchers found that the way galaxies cluster is consistent with our standard model of gravity and the predictions from Einstein’s theory of General Relativity.

A complex analysis of the first year of data from DESI provides one of the most stringent tests yet of General Relativity and how gravity behaves at cosmic scales.

Looking at galaxies and how they cluster throughout time reveals how cosmic structure grows, which lets DESI test theories of modified gravity – an alternative explanation for our universe’s accelerating expansion.

DESI is managed by the US Department of Energy’s (DOE) Lawrence Berkeley National Laboratory (Berkeley Lab). UK involvement in DESI includes the University of Portsmouth, Durham University, and UCL as full member institutions, together with individual researchers at the universities of Cambridge, Edinburgh, St Andrews, Sussex, and Warwick.    READ MORE...

Tesla Magnet Lowers Nuclear Fusion Costs

A new 20 Tesla Superconducting magnet reduces the cost per watt of a fusion reactor by a factor of almost 40. MIT worked with Commonwealth Fusion Systems, a startup with over $2 billion in funding. The funders of CFS include Temasek Holdings (Singpore), the U.S. Department of Energy, Tiger Global Management, Bill Gates, Google and Breakthrough Energy Ventures.

Commercial nuclear fusion now has a chance of being economical.

In the last few years, a newer material nicknamed REBCO, for rare-earth barium copper oxide, was added to fusion magnets, and allows them to operate at 20 kelvins, a temperature that despite being only 16 kelvins warmer, brings significant advantages in terms of material properties and practical engineering.   READ MORE...

A Quantum Enigma

Scientists have discovered that tantalum, a superconducting metal, significantly improves the performance of qubits in quantum computers. By using x-ray photoelectron spectroscopy, they found that the tantalum oxide layer on qubits was non-uniform, prompting further investigations on how to modify these interfaces to boost overall device performance.





Researchers decode the chemical profile of tantalum surface oxides to enhance understanding of loss mechanisms and to boost the performance of qubits.

Whether it’s baking a cake, constructing a building, or creating a quantum device, the caliber of the finished product is greatly influenced by the components or fundamental materials used. In their pursuit to enhance the performance of superconducting qubits, which form the bedrock of quantum computers, scientists have been probing different foundational materials aiming to extend the coherent lifetimes of these qubits.

Coherence time serves as a metric to determine the duration a qubit can preserve quantum data, making it a key performance indicator. A recent revelation by researchers showed that the use of tantalum in superconducting qubits enhances their functionality. However, the underlying reasons remained unknown – until now.


Scientists from the Center for Functional Nanomaterials (CFN), the National Synchrotron Light Source II (NSLS-II), the Co-design Center for Quantum Advantage (C2QA), and Princeton University investigated the fundamental reasons that these qubits perform better by decoding the chemical profile of tantalum.


The results of this work, which were recently published in the journal Advanced Science, will provide key knowledge for designing even better qubits in the future. CFN and NSLS-II are U.S. Department of Energy (DOE) Office of Science User Facilities at DOE’s Brookhaven National Laboratory. C2QA is a Brookhaven-led national quantum information science research center, of which Princeton University is a key partner.     READ MORE...

Matter Transformation

Physicists at the RHIC are studying phase changes in nuclear matter from gold ion collisions to identify a critical point in these transformations. Their research, involving recreating and examining the transition of quark-gluon plasma, a state of matter present after the Big Bang, suggests that fluctuations in the formation of lightweight nuclei could indicate this critical point. Certain data deviations hint at potential fluctuations, but further research is required to confirm a discovery.

Analysis of lightweight nuclei emerging from gold ion collisions offers insight into primordial matter phase changes.

Physicists analyzing data from gold ion smashups at the Relativistic Heavy Ion Collider (RHIC), a U.S. Department of Energy (DOE) Office of Science user facility for nuclear physics research at DOE’s Brookhaven National Laboratory, are searching for evidence that nails down a so-called critical point in the way nuclear matter changes from one phase to another.

New findings from members of RHIC’s STAR Collaboration published in the journal Physical Review Letters hint that calculations predicting how many lightweight nuclei should emerge from collisions could help mark that spot on the roadmap of nuclear phase changes. 

Proof of a critical point—a point where there’s a change in the way nuclear matter transforms from one phase to another—is key to answering fundamental questions about the makeup of our universe.  READ MORE...

Strange Matter Observed

Jefferson Lab’s CEBAF Large Acceptance Spectrometer in Experimental Hall B. 

Credit: DOE’s Jefferson Lab

New findings from Jefferson Laboratory shed light on the process of forming strange matter from ordinary matter.

Nuclear physicists have made a groundbreaking discovery through their unique analysis of experimental data. For the first time ever, they have observed the production of lambda particles, also known as “strange matter,” through a process called semi-inclusive deep inelastic scattering (SIDIS). 

The data obtained also suggests that the building blocks of protons, quarks, and gluons can sometimes march through the nucleus of an atom in pairs referred to as diquarks. The experiment was carried out at the Thomas Jefferson National Accelerator Facility, which is run by the U.S. Department of Energy.

This achievement has been the culmination of many years of hard work. The data that was used in this study was originally gathered in 2004. Lamiaa El Fassi, who is currently serving as an associate professor of physics at Mississippi State University and is the lead researcher of this project, initially analyzed these data while she was working on her thesis project to obtain her graduate degree on a different topic.


Nearly a decade after completing her initial research with these data, El Fassi revisited the dataset and led her group through a careful analysis to yield these unprecedented measurements. The dataset comes from experiments in Jefferson Lab’s Continuous Electron Beam Accelerator Facility (CEBAF), a DOE user facility. 

In the experiment, nuclear physicists tracked what happened when electrons from CEBAF scatter off the target nucleus and probe the confined quarks inside protons and neutrons. The results were recently published in Physical Review Letters.


“These studies help build a story, analogous to a motion picture, of how the struck quark turns into hadrons. In a new paper, we report first-ever observations of such a study for the lambda baryon in the forward and backward fragmentation regions,” El Fassi said.

In like a lambda, out like a pion
Like the more familiar protons and neutrons, each lambda is made up of three quarks.  READ MORE...

Deep Reinforcement Learning

Scientists have taken a key step toward harnessing a form of artificial intelligence known as deep reinforcement learning, or DRL, to protect computer networks.

When faced with sophisticated cyberattacks in a rigorous simulation setting, deep reinforcement learning was effective at stopping adversaries from reaching their goals up to 95 percent of the time. The outcome offers promise for a role for autonomous AI in proactive cyber defense.

Scientists from the Department of Energy's Pacific Northwest National Laboratory documented their findings in a research paper and presented their work Feb. 14 at a workshop on AI for Cybersecurity during the annual meeting of the Association for the Advancement of Artificial Intelligence in Washington, D.C.

The starting point was the development of a simulation environment to test multistage attack scenarios involving distinct types of adversaries. Creation of such a dynamic attack-defense simulation environment for experimentation itself is a win. The environment offers researchers a way to compare the effectiveness of different AI-based defensive methods under controlled test settings.

Such tools are essential for evaluating the performance of deep reinforcement learning algorithms. The method is emerging as a powerful decision-support tool for cybersecurity experts—a defense agent with the ability to learn, adapt to quickly changing circumstances, and make decisions autonomously. While other forms of AI are standard to detect intrusions or filter spam messages, deep reinforcement learning expands defenders' abilities to orchestrate sequential decision-making plans in their daily face-off with adversaries.

Deep reinforcement learning offers smarter cybersecurity, the ability to detect changes in the cyber landscape earlier, and the opportunity to take preemptive steps to scuttle a cyberattack.  READ MORE...

Upgrade to US Power Grid

The grid upgrade, which will decarbonize the power sector and support electrification of transportation and other sectors such as clean energy and charging infrastructure, is a crucial part of reaching the Biden administration’s goal of 100% clean electricity by 2035 and net zero by 2050.

And it can’t come soon enough: 70% of the US grid’s transmission lines and power transformers are over 25 years old. There’s also insufficient transmission capacity, especially transmission that facilitates transfer of power across regions.

As it stands, the power grid is vulnerable to harsh weather, and the new initiative will improve reliability.

The new Better Grid Initiative will make the US power grid more resilient, increase access to affordable and reliable clean energy, and create jobs across industry sectors. The DOE’s summary of the Initiative states:

Under the Building a Better Grid Initiative, DOE will identify critical national transmission needs and support the buildout of long-distance, high-voltage transmission facilities that meet those needs through collaborative transmission planning, innovative financing mechanisms, coordinated permitting, and continued transmission-related research and development. DOE commits to robust engagement on energy justice and collaboration, including with states, American Indian Tribes and Alaska Natives, industry, unions, local communities, and other stakeholders for successful implementation of the program.

The DOE’s notice of intent includes five major points:

• Engaging and collaborating early with states, tribal nations, and stakeholders.
• Enhancing transmission planning to identify areas of greatest need.
• Deploying more than $20 billion in federal financing tools, including through the Bipartisan Infrastructure Law’s new $2.5 billion Transmission Facilitation Progra, m, $3 billion expansion of the Smart Grid Investment Grant Program, and more than $10 billion in grants for states, Tribes, and utilities to enhance grid resilience and prevent power outages. It also taps into existing tools, including the more than $3 billion Western Area Power Administration Transmission Infrastructure Program, and a number of loan guarantee programs through the Loan Programs Office.
• Facilitating an efficient transmission permitting process by coordinating with federal agencies to streamline permitting, using public private partnerships, and designating corridors.
• Performing transmission-related research and development.  READ MORE...