Record Network Sync Beyween National Labs

Record Network Sync Between National Labs

PRESS RELEASE | ARGONNE NATIONAL LABORATORY

Quantum network between two national labs achieves record synch

BY JOHN SPIZZIRRI| JUNE 27, 2022 in anl.gov

Quantum collaboration demonstrates in Chicagoland the first steps toward functional long-distance quantum networks over deployed telecom fiber optics, opening the door to scalable quantum computing.

To test the synchronicity of two clocks — one at Argonne and one at Fermilab — scientists transmitted a traditional clock signal (blue) and a quantum signal (orange) simultaneously between the two clocks. The signals were sent over the Illinois Express Quantum Network. Researchers found that the two clocks remained synchronized within a time window smaller than 5 picoseconds, or 5 trillionths of a second. (Image by Lee Turman, Argonne National Laboratory.)

The world awaits quantum technology. Quantum computing is expected to solve complex problems that current, or classical, computing cannot. And quantum networking is essential for realizing the full potential of quantum computing, enabling breakthroughs in our understanding of nature, as well as applications that improve everyday life.

But making it a reality requires the development of precise quantum computers and reliable quantum networks that leverage current computer technologies and existing infrastructure.

“To have two national labs that are 50 kilometers apart, working on quantum networks with this shared range of technical capability and expertise, is not a trivial thing.” — Panagiotis Spentzouris, head of the Quantum Science Program at Fermilab

Recently, as a sort of proof of potential and a first step toward functional quantum networks, a team of researchers with the Illinois‐Express Quantum Network (IEQNET) successfully deployed a long-distance quantum network between two U.S. Department of Energy (DOE) laboratories using local fiber optics.

The experiment marked the first time that quantum-encoded photons — the particle through which quantum information is delivered — and classical signals were simultaneously delivered across a metropolitan-scale distance with an unprecedented level of synchronization.

The IEQNET collaboration includes the DOE’s Fermi National Accelerator and Argonne National laboratories, Northwestern University and Caltech. Their success is derived, in part, from the fact that its members encompass the breadth of computing architectures, from classical and quantum to hybrid.

“To have two national labs that are 50 kilometers apart, working on quantum networks with this shared range of technical capability and expertise, is not a trivial thing,” said Panagiotis Spentzouris, head of the Quantum Science Program at Fermilab and lead researcher on the project. ​“You need a diverse team to attack this very difficult and complex problem.”

And for that team, synchronization proved the beast to tame. Together, they showed that it is possible for quantum and classical signals to coexist across the same network fiber and achieve synchronization, both in metropolitan-scale distances and real-world conditions.

Classical computing networks, the researchers point out, are complex enough. Introducing the challenge that is quantum networking into the mix changes the game considerably.

When classical computers need to execute synchronized operations and functions, like those required for security and computation acceleration, they rely on something called the Network Time Protocol (NTP). This protocol distributes a clock signal over the same network that carries information, with a precision that is a million times faster than a blink of an eye.  ...  '  

Exascale Supercomputer Can Do a Quintillion Calculations a Second

 Supercomputer advances as well

Exascale Supercomputer Can Do a Quintillion Calculations a Second

Scientific American, Sarah Scoles, , ORNL, February 9, 2023

Oak Ridge National Laboratory's Frontier supercomputer, the world's first declared exascale computer, can perform one quintillion calculations per second and is 2.5 times faster than the world's second-fastest computer. Frontier, which came online last year, will soon be joined by exascale supercomputers El Capitan at the U.S. Department of Energy’s Lawrence Livermore National Laboratory and Aurora at Argonne National Laboratory. While the primary goal of these devices is to run calculations to help maintain the nuclear weapons stockpile overseen by the U.S. Department of Energy's National Nuclear Security Administration, they also will be used to solve intractable problems in pure science.Semantic Web For The Working Ontologist, Third Edition: Effective Modeling In RDFs And Owl  .... 

Solid State Vehicle Batteries

 New directions in battery power for cars,   I have senn nasty examples of flaming wrecks, will ehi remove that danger.

Home/News/The Holy Grail of Electric Vehicles: Solid-State Batteries/Full Text

ACM NEWS

The Holy Grail of Electric Vehicles: Solid-State Batteries, By R. Colin Johnson

Commissioned by CACM Staff, February 7, 2023

Unlike flammable liquid-core Li-ion batteries, Blue Current’s solid-core silicon elastic composite solid-state batteries are smaller, safer, and will last the lifetime of an electric vehicle.

Rechargeable batteries have become the lifeblood of electronics, enabling the mobile revolution. Unfortunately, today's rechargeable batteries incorporate flammable liquid cores. That could change soon, however by switching to rechargeable batteries that have solid cores with nothing to spill, nothing to catch on fire, nothing to potentially explode.

The first rechargeable battery was invented in the mid-19th century, and replaced the crank handle on the front of Model Ts— the lead-acid battery, which is based upon a simple liquid sulfuric acid core. Because of their low cost and relatively large power-to-weight ratio, these batteries still provide the spark that starts today's internal combustion engines (ICEs).

The more advanced liquid-core lithium-ion (Li-ion) batteries powering everything from smartphones to electric vehicles (EVs) are more expensive than lead-acid batteries, but they are worth it because they are lighter and smaller than lead-acid batteries providing the same amount of power, making them more suitable for mobile devices. Even the flammable liquid cores that make Li-ion batteries less safe than the liquid cores of lead-acid batteries are tolerated because of their reduced size.

According to the U.S. Department of Energy (DoE) Joint Center for Energy Storage Research (JCESR), an Energy Innovation Hub led by DOE's Argonne National Laboratory, the Li-ion battery's flammable liquid core is on its way out. Not only is it flammable, but it also creates a toxic-waste disposal problem, introducing increasingly complex manufacturing problems and making the cost of electric vehicles (EVs) almost prohibitively high.

To remedy the problem, Argonne National Labs created JCESR, which designed a new generation of batteries with non-liquid solid cores — in the solid "state"—that are smaller, have higher energy density, and yet promise to return to the safety, ease of manufacturing, and lower cost of lead-acid batteries (once they are in mass production). Solid-state batteries were heralded as the "holy grail of batteries" — their solid-state core is the perfect complement to solid-state electronics — in the Technology Outlook 2030 report by market research firm DNV (Det Norske Veritas, which means "the Norwegian truth"). ... '

Scientists Use Machine Learning to Accelerate Materials Discovery

 The considerable value of materials discovery.

Scientists Use Machine Learning to Accelerate Materials Discovery

By Argonne National Laboratory, October 6, 2022

The final product of the machine learning algorithm: metastable phase diagrams for carbon.

Credit: Argonne National Laboratory

Scientists at the U.S. Department of Energy's Argonne National Laboratory have recently demonstrated an automated process for identifying and exploring promising new materials by combining machine learning and high performance computing. The approach could help accelerate the discovery and design of useful materials.

Using the single element carbon as a prototype, the algorithm predicted the ways in which atoms order themselves under a wide range of temperatures and pressures to make up different substances. From there, it constructed a series of what scientists call phase diagrams — a kind of map that helps guide their search for new and useful states of matter. The study is published in Nature Communications.

"We trained a computer to probe, question, and learn how carbon atoms could be organized to create phases that we might not find on earth or that we don't fully understand, thereby automating a whole step in the materials development process," says Pierre Darancet, an Argonne scientist and author on the study. "The more of this process a computer can handle on its own, the more materials science we can get done."

From Argonne National Laboratory  View Full Article   

And More Skin, Now for Health Monitoring

Argonne at work. 

Skin-Like Electronics Could Monitor Health Continuously

Argonne National Laboratory

Joseph E. Harmon, November 16, 2022

Scientists at the U.S. Department of Energy's Argonne National Laboratory, the University of Chicago, China's Tongji University, and the University of Southern California are developing flexible, wearable electronics that can monitor the wearer's health. The researchers created a skin-like neuromorphic chip from a plastic semiconductor film integrated with stretchable gold nanowire electrodes. In one experiment, the researchers assembled and trained an artificial intelligence device to differentiate healthy electrocardiogram signals from signals indicating health problems, which it did with more than 95% accuracy. The researchers also analyzed the plastic semiconductor under X-rays, in order to better understand its structure.  ... ' 

Ancient Art Meets AI

 Reported on this before,   unexpected connection.

Ancient Art Meets AI for Better Materials Design

Argonne National Laboratory, John Spizzirri, April 7, 2022

University of Southern California (USC) researchers combined kirigami, the ancient Japanese art of paper cutting, with autonomous reinforcement learning to help improve materials design. In an effort to create a two-dimensional molybdenum disulfide structure embedded with electronics that can stretch while remaining stable, the researchers determined that a series of precise cuts could enable the thin material to stretch up to 40%. To determine the correct combination of cuts, the researchers performed simulations on the Theta supercomputer at the U.S. Department of Energy's Argonne National Laboratory. The model was trained on 98,500 simulations of kirigami design strategies involving one to six cuts; even without additional training data, it determined in a matter of seconds that 10 cuts would provide more than 40% stretchability. USC's Pankaj Rajak said, "It learned something the way a human learns, and used its knowledge to do something different."

Kirigami and AI For Materials Design

Most interesting, had seen this reported on before, worked with Argonne in the big enterprise :

Ancient art of kirigami meets AI for better materials design  in TechXplore

by John Spizzirri, Argonne National Laboratory

Kirigami is the Japanese art of paper cutting. Likely derived from the Chinese art of jiǎnzhǐ, it emerged around the 7th century in Japan, where it was used to decorate temples. Still in practice today, the kirigami artist uses one piece of paper to cut decorative designs, like birds and fish or the more intricate and popular snowflake.

But, this ancient art, which relies on exacting cuts to determine or replicate patterns, is finding more modern and practical applications in electronics. Specifically, in the manufacture of 2D stretchable materials that can play host to wearable electronics, like electronic skins for health monitoring.

The process combines the art of kirigami with an artificial intelligence technique called autonomous reinforcement learning. And to better synchronize the old with the new, researchers from the University of Southern California use the computing power available to them at the U.S. Department of Energy's (DOE) Argonne National Laboratory.

Reinforcement learning relates to learning actions that impart a reward or specific outcome. For example, through a combination of observation, repetition and innate ability, a baby giraffe learns to stand, walk and even run on the day it is born. This helps it find food and avoid danger very quickly.

"This is complex planning, it's learning," says Pankaj Rajak, a lead member of this project and a former postdoc at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science user facility. "The question is, can we use a similar behavior in materials design, like in this kirigami, where your objective is to create a more structured material that is highly stretchable, one cut at a time. It's a smart strategy for figuring out where the cuts should go."

The researchers set out to create a 2D molybdenum disulfide structure embedded with electronics, like a semiconductor device, that can stretch but remain stable.

Experimental scientists found that a deliberate series of exacting cuts would allow the atomically thin material to stretch considerably, upwards of 40%. But, there were a lot of possible combinations of cuts. So, what information did the AI program need to know to get the right combinations?

To provide the program with some starting data—like the environmental observations of a giraffe—Rajak conducted 98,500 simulations that consisted of a range of one to six cuts with different lengths that determined stretchability.   ....'

Materials Innovation at Argonne

 New looks at innovation with AI and HPC at Argonne.

Automatic Database Creation for Materials Discovery: Innovation From Frustration

Argonne National Laboratory  by John Spizzirri

Scientists at the U.S. Department of Energy's Argonne National Laboratory and the U.K.'s University of Cambridge have developed a method that generates automatic databases to support specific scientific disciplines, using artificial intelligence and high-performance computing (HPC). The technique can assemble databases via natural language processing (NLP) and HPC, most of which was performed at the Argonne Leadership Computing Facility. The team built a database on both material structures and material properties, using the NLP ChemDataExtractor data-mining application. Cambridge's Jacqueline Cole said, "It's probably the first such compilation of a database on such a massive scale, with 5,380 like-for-like pairs of experimental and calculated data. And because it's such a large amount, it serves as a repository in its own right and really opens the door to predicting new materials."

Partnership that Revolutionized Battery Research at Argonne

Big believed in partnerships.   Some recent conversations have further strengthened that.   My company used to be a big maker of batteries, but it seems never took them much further.

The historical partnership that revolutionized battery research at Argonne
by Joan Koka, Argonne National Laboratory

Argonne scientists Jason Croy, Manar Ishwait and Michael Murphy assemble lithium-ion battery electrodes for testing. Credit: Mark Lopez / Argonne National Laboratory
Researchers around the world are on the hunt to find cheaper, better lithium-ion battery materials to power large scale machines, such as electric vehicles. One of their goals is to find alternative lithium-metal-oxide electrodes to those containing cobalt, an element common within phone and laptop batteries but too expensive and short on capacity to propel electric vehicles over long distances.


For decades, researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory have taken part in the pursuit to uncover battery materials that perform as well as, if not better than, the ones we use today. Among the materials they're investigating are manganese-rich compounds, because manganese is abundant and inexpensive; lithium-manganese oxides are also thermally safer to use, but not as energy dense as their cobalt counterparts.

The laboratory's study of manganese-rich materials is shaped by the work that Argonne Emeritus Fellow Michael Thackeray has been doing since the early 1980s. While a postdoc at Oxford University in 1981-1982, Thackeray worked alongside battery scientist John Goodenough, one of the Nobel-prize winning architects of the modern lithium-cobalt-oxide battery.The historical partnership that revolutionized battery research at Argonne
by Joan Koka, Argonne National Laboratory

Argonne scientists Jason Croy, Manar Ishwait and Michael Murphy assemble lithium-ion battery electrodes for testing. Credit: Mark Lopez / Argonne National Laboratory

Researchers around the world are on the hunt to find cheaper, better lithium-ion battery materials to power large scale machines, such as electric vehicles. One of their goals is to find alternative lithium-metal-oxide electrodes to those containing cobalt, an element common within phone and laptop batteries but too expensive and short on capacity to propel electric vehicles over long distances.

For decades, researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory have taken part in the pursuit to uncover battery materials that perform as well as, if not better than, the ones we use today. Among the materials they're investigating are manganese-rich compounds, because manganese is abundant and inexpensive; lithium-manganese oxides are also thermally safer to use, but not as energy dense as their cobalt counterparts.

The laboratory's study of manganese-rich materials is shaped by the work that Argonne Emeritus Fellow Michael Thackeray has been doing since the early 1980s. While a postdoc at Oxford University in 1981-1982, Thackeray worked alongside battery scientist John Goodenough, one of the Nobel-prize winning architects of the modern lithium-cobalt-oxide battery.... "

Supercomputers at the Exascale

Continued work on faster and better solutions to hard problems.   Still think its mostly about designing and delivering better software in context and to scale.

Intel and Argonne National Lab on 'exascale' and their new Aurora supercomputer
The scale of supercomputing has grown almost too large to comprehend, with millions of compute units performing calculations at rates requiring, for the first time, the exa prefix — denoting quadrillions per second. How was this accomplished? With careful planning... and a lot of wires, say two people close to the project.Having noted the news that Intel and Argonne National Lab were planning to take the wrapper off a new exascale computer called Aurora (one of several being built in the U.S.) earlier ... "

Argonne Makes Biggest File Transfer

Impressive, as suggested, useful for very large combinatorial problems with related data.

Argonne Team Makes Largest Single File Transfer in History
By Oliver Peckham in DataNami

A team of scientists at Argonne National Laboratory has broken a data transfer record by moving a staggering 2.9 petabytes of data for a research project.

The data – from three large cosmological simulations – was generated and stored on the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF), which is currently rated as the world’s fastest supercomputer on the Top500 list at nearly 149 Linpack petaflops.

“We carried out three different simulations on Summit (each simulation resulted in a file transfer of 2-3PB) to model three different scenarios of the makeup of the Universe,” said Dr. Katrin Heitmann, a physicist at Argonne and lead researcher on the project. “We are trying to understand the subtle differences in the distribution of matter in the Universe when we change the underlying model slightly.”  ... '  

Cloaking Resource Operations Data in the Cloud

Fascinating play.  How this differ from methods like blockchains?  Maybe better than BC methods?

Creating a Cloak for Grid Data in the Cloud   By Argonne National Laboratory 

Delivering modern electricity is a numbers game. From power plant output to consumer usage patterns, grid operators juggle a complex set of variables to keep the lights on. Cloud-based tools can help manage all of these data, but utility owners and system operators are concerned about security. That concern is keeping them from using the cloud—a collective name for networked Internet computers that provide scalable, flexible, and economical computing power.

Scientists at the U.S. Department of Energy's Argonne National Laboratory are developing and deploying tools to facilitate cloud computing for grid operations and planning. A framework being developed at Argonne masks sensitive data, allowing grid operators to perform complex calculations in the cloud to determine where and when to dispatch resources. By facilitating these calculations without compromising data security and integrity, the framework helps grid operators take the electricity system into the future while avoiding costly investments in computer infrastructure. ... " 

Reducing Quantum Noise

Worked with folks at Argonne, impressive group.   Regarding using simulations or agent process for improved understanding of process.   Data lost to noise is an interesting area of research.  Predicting future 'noise' also useful in analyses?    Information can also be found in noise.

Argonne Researchers Develop Method to Reduce Quantum Noise 
Argonne National Laboratory
Joe Harmon; Diana Anderson

Argonne National Laboratory (ANL) researchers have developed a technique for reducing the effects of "noise" in quantum information systems. The method retrieves data "lost" to noise via repetition of the quantum process with slightly variable noise characteristics, then analyzes the results. After collecting results by running the process many times in sequence or parallel, the researchers built a hypersurface, where one axis represents the result of a measurement, and the other two or more axes stand for different noise parameters. The hypersurface returned an estimate of the noise-free observable, as well as information about the impact of each noise rate. The Bebop high-performance computing cluster at ANL's Laboratory Computing Resource Center was used to execute simulations that helped refine and demonstrate the technique in scenarios that are currently unavailable with quantum hardware. .... " 

Portal for Scientific Discovery

Augmentation for discovery is something we examined for research.

Networking, Data Experts Design a Better Portal for Scientific Discovery
Lawrence Berkeley National Laboratory

Scientists from the U.S. Department of Energy's Energy Sciences Network (ESnet) and the University of Chicago and Argonne National Laboratory's Globus team have designed a new data portal to make information sharing faster, more reliable, and more secure. "Our new design preserves...ease of use, but easily scales up to handle the huge amounts of data associated with today's science," says ESnet's Eli Dart. The new portal design is based on Dart's Science DMZ, a high-performance network framework that connects large-scale data servers directly to high-speed networks and increasingly is used by research institutions for data transfer management. Another key platform is the cloud-based Globus service enabling developers to outsource responsibility for complex tasks such as authentication, authorization, data movement, and data sharing. An important system element is Globus Connect, which lets the Globus service transfer data to and from the computer using high-performance protocols as well as HTTPS for direct access. ....  "

Michael North - Agent Models Argonne Labs

Michael J. North, MBA, Ph.D.
https://www.linkedin.com/in/drmichaelnorth

Group Leader
Integrated Analytics Group
Systems Science Center
Global Security Sciences Division
Argonne National Laboratory
9700 S. Cass Avenue
Argonne, IL 60439-4854
north@anl.gov
www.gss.anl.gov
630-252-6234

Senior Fellow
Computation Institute
The University of Chicago
Searle Laboratory
5735 South Ellis Avenue
Chicago, IL 60637-1403
north@uchicago.edu
www.ci.uchicago.edu
773-702-3946

Smart Cities and their Data

A look at the new Smart City, and its implications.  In the CACM.

" ... The flood of information could also create new challenges, according to Pete Beckman, director of the Exascale Technology and Computing Institute at Argonne and a leader in the Array of Things project. "We'll have so much data about our smart cities, but will we have the operating system?" asks Beckman.

Overall, the changes to these smart cities will be incremental, whether they are driven by researchers like Beckman and Catlett, urban planners, private innovators, or some combination. "You're not going to wake up one day and live in the city of the future," says Townsend. "Cities are systems of systems. It takes time to bring about large-scale change, but in the future I think we will be living in cities that fundamentally operate differently."  ... " 

See more about the Array of things project by Argonne and Chicago.

Jaron Lanier Flips on Wal-Mart, Apple and Google

We met computer scientist Jaron Lanier while doing work with the Institute for the Future.  In the Edge he talks about the local global flip.  Quite a long rant on the effect of corporations leveraging the network, collectivism and advanced computing.   "If you aspire to use computer network power to become a global force through shaping the world instead of acting as a local player in an unfathomably large environment, when you make that global flip, you can no longer play the game of advantaging the design of the world to yourself and expect it to be sustainable. The great difficulty of becoming powerful and getting close to a computer network is: Can people learn to forego the temptations, the heroin-like rewards of being able to reform the world to your own advantage in order to instead make something sustainable?"  

GIS and Agent Based Modeling

An article from a while back that addresses how virtual worlds,GIS and agent based modeling can be linked together for research applications. Via Dave Cohen. This blog has covered these and related topics for some time.

Here are a few examples of posts on work in the enterprise I have been involved in. For example, a paper published that used agent based modeling to solve difficult market models, in conjunction with Argonne National Labs. A book published that does a good job of describing a number of models that can be used as examples. Finally, a local company, Thinkvine, which is using agent models to understand the interaction between promotions and results.

The GIS interaction is also something we also explored, in 2004 we were finalists for the Edelman prize in the use of interactive GIS to solve supply chain models. I still remain closely connected to location and model based applications. Need to know more? Contact me, email address in the left column.

Agent-Based Consumer Market Modeling

A number of my former colleagues at Procter & Gamble have co-authored a paper with some smart people I met at Argonne National Labs. Abstract below. Fascinating application of agents to markets. With very interesting details. To appear in Complexity Magazine. Congrats for its publication to everyone.

Multiscale agent-based consumer market modeling
Michael J. North 1 , Charles M. Macal 1, James St. Aubin 2, Prakash Thimmapuram 3, Mark Bragen 2, June Hahn 4, James Karr 4, Nancy Brigham 4, Mark E. Lacy 4, Delaine Hampton 4
1Center for Complex Adaptive Agent Systems Simulation, Argonne, Illinois 60439
2Modeling, Simulation, and Visualization Group, Argonne, Illinois 60439
3Center for Energy, Environmental, and Economic Systems Analysis, Argonne National Laboratory, Argonne, Illinois 60439
4The Procter & Gamble Company, Cincinnati, Ohio 45202

Abstract
Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression-based models, logit models, and theoretical market-level models, such as the NBD-Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method - agent-based modeling - shows promise for addressing these issues. Agent-based models use business-driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system-level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent-based modeling to develop a multi-scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings.

Managing Business Complexity

Re-Discovered: Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation by Michael J. North and Charles M. Macal . Read parts of this back in 2007 when it was published as an introduction. Now I am re-examining the use of Agent-Based Modeling (ABM) and the book forms an excellent study of the methodology and a number of applied examples. Both authors work at Argonne National Labs and we very successfully used their consulting services. Instructional pieces in this area are fragmented, but this is the only the book I know that puts it all together. I suggest at the least the first few chapters and browsing the rest for examples.