Quantum Annealing Can Beat Classical Computing in Limited Cases

 Have mentioned Quantum Annealing methods here a number of time.  And D-Wave, a successful effort in delivering related capabilities as Quantum solutions.     Recall our short interaction with them and this system.    We also worked with Los Alamos Labs, below described their work.     Based on this report I do do not know how they relate.   May follow up. 

Quantum Annealing Can Beat Classical Computing in Limited Cases

By Los Alamos National Laboratory, August 17, 2022

Quantum annealing computers can run algorithms faster than classical computers in certain instances, but typically not when time is limited.

Nikolai Sinitsyn and Bin Yan at the U.S. Department of Energy's Los Alamos National Laboratory designed an analytical strategy to demonstrate a simple untuned process that solves any computational problem considered by a quantum annealing system, with computational accuracy characterized at any point during runtime. However, this accuracy is rarely superior to classical algorithmic performance because efficient quantum computing depends on quantum effects, while many quantum histories interfere to magnify the useful information in the final state.

Without fine-tuning, the proper interference becomes unlikely, though there are exceptions which leave the niche for superior quantum computing.

From Los Alamos National Laboratory

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ShakeAlert Earthquake Warning System

 Were loosely involved in the testing of this warning system. Up to 10 second pre alert noted.

Home/News/Seconds Before Earthquake Rattled California, Phones... 

ACM TECHNEWS

Seconds Before Earthquake Rattled California, Phones Got Vital Warning  By The Guardian (U.K.)

An early-alert system managed by the U.S. Geological Survey (USGS) on Monday warned Californians of a 6.2-magnitude earthquake by phone, seconds before it struck.

The ShakeAlert system issues warnings through various agencies and applications, including Google's Android operating system.   USGS sensors feed information bundled into a data package that is displayed on phones within seconds; some alert apps are available for download, but even some who had no such app on their phones received alerts.

ShakeAlert sent quake warnings to about 500,000 phones before the tremors began.  "We got some reports from folks that they got up to 10 seconds' warning before they felt shaking. That's pretty darn good," said the USGS' Robert de Groot.

From The Guardian (U.K.)

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See also:

Using Sparse Data to Predict Lab Quakes  By Los Alamos National Laboratory,  December 30, 2021

A Training Proof for Quantum AI

Technical finding regarding CNN and the ability to train.     Applicability to discovering new materials. 

Breakthrough Proof Clears Path for Quantum AI

Los Alamos National Laboratory News, October 15, 2021

Scientists at the U.S. Department of Energy's Los Alamos National Laboratory (LANL) have devised a proof that convolutional neural networks can always be trained on quantum computers, avoiding the threat of "barren plateaus" in optimization problems. LANL's Marco Cerezo said while a barren plateau eliminates any possibility of quantum speedup or advantage, "We proved the absence of barren plateaus for a special type of quantum neural network. Our work provides trainability guarantees for this architecture, meaning that one can generically train its parameters." LANL's Patrick Coles said, "With this guarantee in hand, researchers will now be able to sift through quantum-computer data about quantum systems and use that information for studying material properties or discovering new materials, among other applications." ... ' 

AI to Keep the Lights on?

 This deserves a deeper dive, especially if you are into complex modeling of the operation of systems.  The contest is over, but by examining the overview of the statement of the problem, I was impressed.  I am continuing to review.   Was particularly interested if they could model and minimize  or potentially re design Power Grids for events like solar CMEs. An ultimate grid security issue. Could this be a starting point? Anyone know?  We worked with Los Alamos and they were impressive. 

Los Alamos scientists take top prizes in national competition to help improve electrical grid

Artificial intelligence-driven algorithms could help keep the lights on

Los Alamos, N.M., Oct. 4, 2021—Two scientists at Los Alamos National Laboratory took top prizes in a national competition for developing algorithms to help improve the resiliency and efficiency of the electrical grid. The algorithm developed by Hassan Hijazi of the Applied Mathematics and Plasma Physics Group took first place in all four divisions, while the one developed by Carleton Coffrin of the Laboratory’s Information Systems and Modeling Group placed second in two of the four divisions. Their work outperformed 14 other entries in the competition:   https://gocompetition.energy.gov/   funded by Advanced Research Projects Agency–Energy (ARPA-E), a United States government agency that promotes and funds research and development of advanced energy technologies.

“Grid security is a national security issue, which is why this is important work for Los Alamos,” said Nancy Jo Nicholas, associate Laboratory director for Global Security at Los Alamos. “Every five minutes, optimization problems arise in the U.S. electrical grid that require a mathematical solution. Hassan’s and Carleton’s achievement will help advance national efforts to create a more reliable, resilient, and secure electrical grid.”  ... 

Foiling illicit cryptocurrency mining with artificial intelligence

Again matching, finding patterns that are malicious.

Foiling illicit cryptocurrency mining with artificial intelligence
by James Riordon, Los Alamos National Laboratory in TechXplore

Los Alamos National Laboratory computer scientists have developed a new artificial intelligence (AI) system that may be able to identify malicious codes that hijack supercomputers to mine for cryptocurrency such as Bitcoin and Monero.

"Based on recent computer break-ins in Europe and elsewhere, this type of software watchdog will soon be crucial to prevent cryptocurrency miners from hacking into high-performance computing facilities and stealing precious computing resources," said Gopinath Chennupati, a researcher at Los Alamos National Laboratory and co-author of a new paper in the journal IEEE Access. "Our deep learning artificial intelligence model is designed to detect the abusive use of supercomputers specifically for the purpose of cryptocurrency mining." ... " 

More information: Poornima Haridas et al, Code Characterization with Graph Convolutions and Capsule Networks, IEEE Access (2020). DOI: 10.1109/ACCESS.2020.3011909

Quantum Navigation?

I am skeptical that a quantum computer is necessary for this kind of shortest route navigation.  But interesting claim, and a real problem.  Will examine further.  Saw the D-Wave special kind of  annealing application of quantum computing early on.   Continue to follow

Volkswagen to Test Quantum Navigation App in Real Traffic
The Wall Street Journal
Sara Castellanos
October 31, 2019

Volkswagen will test a quantum navigation app in Portugal next week, with plans to eventually incorporate its capabilities into automobiles. Nine buses shuttling passengers between Lisbon's Web Summit conference and other metropolitan areas will have iPads loaded with the app, which features technology from Canada’s D-Wave Systems. The app employs cloud-based quantum-computing services to calculate the swiftest route for each bus in near-real time, in order to minimize traffic congestion and shorten travel times. While a predictive analytics tool on a classical computer will identify which of 26 bus stops probably have especially high rider numbers 45 minutes ahead of time, a quantum computer will map out the fastest route for each bus, accounting for millions of real-time data points about congestion and ridership demand in milliseconds. Said Scott Pankin of Los Alamos National Laboratory, “What’s exciting about this work is that it’s being applied in the real world.” 

D-Wave Still in the Race for Quantum

Have been following D-Wave's work since their inception.     We also worked with Los Alamos in the area of dealing with rare maintenance events.   See tag below.

Nuclear weapons lab buys D-Wave's next-gen quantum computer

Los Alamos National Laboratory will install D-Wave's 5,000-qubit Advantage system in 2020.

 It's been a busy time in quantum computing: IBM announced its biggest quantum computer so far, and Google reportedly has cracked a problem with its quantum computer faster than a conventional computer could. Now D-Wave, a rival with a different approach to the technology, has announced that nuclear weapons research site Los Alamos National Laboratory (LANL) is the first customer for its next-generation machine.

Quantum computers are a totally different breed of machine than the classical computers that power everything from your smartphone to Amazon's vast e-commerce operation. Quantum computers rely on the weird physics of the very small to perform calculations classical machines  can't solve -- at least in principle. So far, the technology is very, very experimental..... " 

https://en.wikipedia.org/wiki/D-Wave_Systems:  from the Wikipedia:


" .... On May 11, 2011, D-Wave Systems announced D-Wave One, described as "the world's first commercially available quantum computer", operating on a 128-qubit chipset[10] using quantum annealing (a general method for finding the global minimum of a function by a process using quantum fluctuations)[11][12][13][14] to solve optimization problems.   ... " 

Simulating Molecular Motion with Neural Networks

Have now seen several examples of using neural nets to simulate complex systems by generating a model from data.    Thought provoking example I am following up on.

Researchers Cast Neural Nets to Simulate Molecular Motion 
Los Alamos National Laboratory News
By Nancy Ambrosiano      July 2, 2019

The U.S. Department of Energy's Los Alamos National Laboratory (LANL), the University of North Carolina at Chapel Hill, and the University of Florida demonstrated that artificial neural nets can be taught to encode quantum mechanical laws that define molecular motion, potentially advancing simulations across many disciplines. Said LANL's Justin Smith, "We can now model materials and molecular dynamics billions of times faster compared to conventional quantum methods, while retaining the same level of accuracy." The researchers developed a machine learning technique to build empirical potentials—atomic dynamics descriptions that follow classical physical and Newtonian laws—from data collected about millions of compounds. The transfer learning technique can be applied to new molecules in milliseconds .... " 

Researchers cast neural nets to simulate molecular motion
Machine learning allows quantum mechanics to be efficiently applied to molecular simulations for drug development, detonation physics and more .... " 


Publication:   J. S. Smith, B. T. Nebgen, R. Zubatyuk, N. Lubbers, C. Devereux, K. Barros, S. Tretiak, O. Isayev, A. E. Roitberg, “Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning,” Nature Communications 10.1038/s41467-019-10827-4 (2019)  ..... " 

Technical paper:  https://www.nature.com/articles/s41467-019-10827-4

Integrated Work System

A conversation with former enterprise colleagues led me to this piece on reliability innovation I had a small part in.    See the tag links to Los Alamos Labs, which was also involved.  Here to pass this on to my readers for reference, worth examining.

Pointer to some of the above work in R&D Magazine.
This was originally offered for use by KPMG Consulting. in 2005.

EY and P&G Alliance  and see also @EY_Alliances
What will operational excellence look like in your organization’s future?

Despite investments in lean manufacturing, Six Sigma and total productivity maintenance, companies are struggling to achieve a breakthrough in manufacturing productivity. EY and P&G have combined their manufacturing excellence capabilities to bring a significantly different approach to attaining higher levels of manufacturing performance.

P&G’s Integrated Work System (IWS) is a proprietary way of improving manufacturing reliability, reducing costs and elevating productivity. IWS is a disruptive way of working predicated on two primary principles: the drive to zero losses and 100 percent employee ownership. The EY and P&G alliance combines the Integrated Work System with the global EY manufacturing performance improvement experience and P&G certified consultants to help clients improve performance via sustainable change and transformation.  ..... 

Newsroom
  
Procter & Gamble (P&G) has recognized EY as one of twelve top performing companies to receive its highest honor of being named Excellence Award winners and External Business Partner of the Year at the 2016 P&G External Business Partner of the Year Recognition Dinner, which recognizes exemplary partner collaboration.

Among P&G’s more than 50,000 suppliers and agencies, EY was the only professional services organization to receive the award. EY has now received the P&G Excellence Award six times and the Partner of the Year award three times.

Kristina Rogers, EY Global Consumer Products and Retail Leader, says:

“We are thrilled to be recognized by P&G for EY’s commitment to collaboration. With the industry facing unprecedented disruption, business innovation is critical to meet changing consumer wants and needs and to sustaining profitable growth. We are proud to be a key member of the P&G innovation ecosystem, challenging thinking and helping to deliver on its consumer promise.”

David Taylor, P&G President and CEO, presented the award to EY for engendering strong trust and collaboration through agility and quality advisory services.

Taylor says: “Supplier partners have a key role to play in our ability to deliver. The more integrated and connected P&G and our supplier partners are, the better able we are to be more innovative and productive in meeting consumers’ needs.”   .... "

Predicting Earthquakes with Machine Learning

Broad idea has been around for years.  Are we getting closer?  Gets heavily into accuracy and risk of different kinds of errors here.    We worked with them on machine failure analysis and prediction, which has some similar profiles of failure.

Machine-learning earthquake prediction in lab shows promise  LANL press release. 

A computer science approach using machine learning can predict the time remaining before the fault fails   Listening to faultline’s grumbling gives countdown to future quakes

LOS ALAMOS, N.M., Aug. 30, 2017—By listening to the acoustic signal emitted by a laboratory-created earthquake, a computer science approach using machine learning can predict the time remaining before the fault fails.

“At any given instant, the noise coming from the lab fault zone provides quantitative information on when the fault will slip,” said Paul Johnson, a Los Alamos National Laboratory fellow and lead investigator on the research, which was published today in Geophysical Research Letters.

“The novelty of our work is the use of machine learning to discover and understand new physics of failure, through examination of the recorded auditory signal from the experimental setup. I think the future of earthquake physics will rely heavily on machine learning to process massive amounts of raw seismic data. Our work represents an important step in this direction,” he said.

Not only does the work have potential significance to earthquake forecasting, Johnson said, but the approach is far-reaching, applicable to potentially all failure scenarios including nondestructive testing of industrial materials brittle failure of all kinds, avalanches and other events.

Machine learning is an artificial intelligence approach to allowing the computer to learn from new data, updating its own results to reflect the implications of new information.

The machine learning technique used in this project also identifies new signals, previously thought to be low-amplitude noise, that provide forecasting inform with slow earthquakes on tectonic faults in the lower crust,” Johnson said. “There is reason to expect such signals from Earth faults in the seismogenic zone for slowly slipping faults.” ....  

Machine learning algorithms can predict failure times of laboratory quakes with remarkable accuracy. The acoustic emission (AE) signal, which characterizes the instantaneous physical state of the system, reliably predicts failure far into the future. This is a surprise, Johnson pointed out, as all prior work had assumed that only the catalog of large events is relevant, and that small fluctuations in the AE signal could be neglected.  .... " 

Quantum Dot Energy Extraction

In IEEE Spectrum.  Quantum dot research at Los Alamos points to efficient window coatings that can extract useful energy.

GE Predix Cloud Predicts Machine Failures

We worked on a similar project in collaboration with Los Alamos Labs. In particular to do reliability and failure prediction for systems that were composed of elements that only rarely failed.   So called 'Black Swans'.    This was eventually licensed out via a third party.  Examining the difference between the ideas.   Will report back here with more information.  A related project looked at out of stock condition on a store shelf as a failure that could be predicted by multiple sensory inputs.

Pointer to some of the above work in R&D Magazine.
This was eventually offered for use by KPMG Consulting. in 2005.

In FastCompany:
GE wants to give industrial machines their own social network with Predix Cloud ... GE is selling a new service that promises to predict when a machine will break down, so technicians can preemptively fix it. .... "