Archive for the ‘Quantum Computer’ Category

QuantLR Partners With MedOne to Test and Validate a QKD Solution to Protect Against Quantum Computer Attacks – StartupHub.ai

QuantLR Ltd, an Israel-based Quantum Key Distribution (QKD) company, and MedOne, a leading Israeli data center service provider, have announced the successfuloperationofQuantLRs QKD system with MedOnes Data Centerinfrastructurebetween the cities ofTel Aviv andPetah Tikva.

Quantum Key Distribution (QKD) is the onlyproven technology that provides the ultimate level of security fordata in transit, includingsecurity against any attack or eavesdropping attempts by contemporary, future, classical or quantum-based computers. Another threat that is secured by QKD is a hack now- decrypt later attack where the attacker collects the data now and decrypt in a later stage. This puts a sense of urgency in the implementation of QKD.

This quantum-based technology isespeciallyimportant in a data center environment to secure the information to and from the data center, between data centers, and within the data center itself.

The announcement comes following the recent successful testthat was conducted between the MedOne Tel Aviv and MedOne Petah Tikva facilities, over a distance of more than 35km (21.7 miles). Earlier this year QuantLR managed to exchange keys over longer distances.

The test was led by Dr. Nitzan Livneh, QuantLRs CTO, and Eli Saig, MedOnes CTO.

A single fiber strand was used to carry the quantum information as well as C-band data channels, enabling quantum-safe communication for clients without dark fiber. The system created more than ten 256bit symmetric encryption keys per second, without any flaws.

A QKD solution at an affordable price is critical to solve a major upcoming problem: todays networksecurityrelies on public keycryptographythatishighly vulnerable to cracking. The vast majority of encryption keys in the commercial world are distributed via PKI, but new algorithms and advances in quantum computing will soon provide the capabilities to crack most PKI instances, including RSAand Diffie Hellman methods. This issue is well-known, and Quantum Key Distribution is widely considered the most secure solution for long-term data security, as conventional security solutions approach their end-of-life.

We are delighted to collaborate with a leading data center service provider such as MedOne. Data Centers are a very important use case for QKD and we see an increasing demand from leading players in this market, notesDr. Nitzan Livneh, CTO of QuantLR

Data security has become the most important aspect in a data center offering, and we are planning to be the first data center service provider worldwide that will offer a QKD solution to secure its clients data noted Ronnie Sadeh, CEO of MedOne.

AboutQuantLR:Headquartered in Israel, QuantLRaims to provide versatile cost-effective quantum cryptographic solutions based on quantum key distribution (QKD)technology to protect communicated data. This solution is proven to provide the ultimate level of security against any attack by contemporary, future, classical or quantum-based computers. QuantLRs solutions will be offered to the market as a component embedded within communication hardware vendor products, as well as stand-alone products.

About MedOne:MedOne leads Israels data center market, providing comprehensive hosting services to Israels largest organizations. With several underground data centers spanning over 16,000 square meters (172,000 square feet), MedOne provides hosting, backup and business continuity services with the highest SLA, resiliency and the best standard of security.

QuantLR Contact

Shlomi Cohen, shlomi[at]quantlr.com

Read more here:
QuantLR Partners With MedOne to Test and Validate a QKD Solution to Protect Against Quantum Computer Attacks - StartupHub.ai

Quantum Computing Inc. Unveils Software Breakthrough That Amplifies Quantum Computer Processing Power By Up to 20x – Yahoo Finance

Quantum Computing Inc.

QAmplify Maximizes End-User Investment in Quantum Computing

LEESBURG, Va., June 07, 2022 (GLOBE NEWSWIRE) -- Quantum Computing Inc. (QCI'' or the Company) (NASDAQ: QUBT), a leader in accessible quantum computing, today unveiled QAmplify, a suite of quantum software technologies that expands the processing power of any current quantum computer by as much as 20x. QAmplify is capable of supercharging any quantum computer to solve real-world realistic business problems today. The Company is actively working with customers and partners in scaling the amplification capabilities of its ready-to-run Qatalyst software, which is designed to eliminate the need for complex quantum programming and runs seamlessly across a variety of quantum computers. QCI has filed for patents on QAmplify technology.

Currently there are two primary technology approaches that deliver a wide range of capabilities spanning the current Quantum Processing Unit (QPU) hardware landscape; gate model (e.g. IBM, IonQ, Rigetti, OQC, etc.) and annealing (e.g. D-Wave) quantum computers. Both are limited in the size of problems (i.e., number of variables and complexity of computations) they can process. For example, gate models can typically process from 10-120 data variables, and annealing machines can process approximately 400 variables in a simple problem set. These small problem sets restrict the size of the problems that can be solved by todays QPUs, limiting businesses ability to explore the value of quantum computing.

QCIs patent-pending QAmplify suite of powerful QPU-expansion software technologies overcomes these challenges, dramatically increasing the problem set size that each can process. The QAmplify gate model expansions demonstrated capabilities have been benchmarked at a 500% (5x) increase and the annealing expansion has been benchmarked at up to a 2,000% (20x) increase.

QAmplify maximizes end-user investment in current QPUs by allowing quantum users to transform from science experiments to solving real-world problems without waiting for the quantum hardware industry to catch up. For example, in terms of real-world applications, this means that an IBM quantum computer with QAmplify could solve a problem with over 600 variables, versus the current limit of 127 variables. A D-Wave annealing computer with QAmplify could solve an optimization with over 4,000 variables, versus the current limit of 200 for a dense matrix problem set.

Story continues

It is central to QCIs mission to deliver practical and sustainable value to the quantum computing industry, said William McGann, Chief Operating and Technology Officer of QCI. QCIs innovative software solutions deliver expansive compute capabilities for todays state-of-the-art QPU systems and offer great future scalability as those technologies continually advance. The use of our QAmplify algorithm in the 2021 BMW Group Quantum Computing Challenge for vehicle sensor optimization provided proof of performance by expanding the effective capability of the annealer by 20-fold, to 2,888 qubits.

To learn more about QCI and how Qatalyst can deliver results for your business today, visit http://www.quantumcomputinginc.com.

About Quantum Computing Inc.Quantum Computing Inc. (QCI) (NASDAQ: QUBT) is a full-spectrum quantum software and hardware company on a mission to accelerate the value of quantum computing for real-world business solutions. The company recently announced its intent to acquire QPhoton, a quantum photonics innovation company that has developed a series of quantum photonic systems (QPS). The combination of QCIs flagship ready-to-run software product, Qatalyst, with QPhotons QPS, sets QCI on a path to delivering a broadly accessible and affordable full-stack quantum solution that can be used by non-quantum experts, anywhere, for real-world industry applications. QCIs expert team in finance, computing, security, mathematics and physics has over a century of experience with complex technologies; from leading edge supercomputing, to massively parallel programming, to the security that protects nations. Connect with QCI on LinkedIn and @QciQuantum on Twitter. For more information about QCI, visit http://www.quantumcomputinginc.com.

Important Cautions Regarding Forward-Looking StatementsThis press release contains forward-looking statements as defined within Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. By their nature, forward-looking statements and forecasts involve risks and uncertainties because they relate to events and depend on circumstances that will occur in the near future. Those statements include statements regarding the intent, belief or current expectations of Quantum Computing Inc. (the Company), and members of its management as well as the assumptions on which such statements are based. Prospective investors are cautioned that any such forward-looking statements are not guarantees of future performance and involve risks and uncertainties, and that actual results may differ materially from those contemplated by such forward-looking statements.

Statements in this press release that are not descriptions of historical facts are forward-looking statements relating to future events, and as such all forward-looking statements are made pursuant to the Securities Litigation Reform Act of 1995. Statements may contain certain forward-looking statements pertaining to future anticipated or projected plans, performance and developments, as well as other statements relating to future operations and results. Any statements in this press release that are not statements of historical fact may be considered to be forward-looking statements. Words such as "may," "will," "expect," "believe," "anticipate," "estimate," "intends," "goal," "objective," "seek," "attempt," aim to, or variations of these or similar words, identify forward-looking statements. Such statements include statements regarding the Companys ability to consummate its planned acquisition of QPhoton, the anticipated benefits of such acquisition, and the Companys ability to successfully develop, market and sell its products. Factors that could cause actual results to differ materially from those in the forward-looking statements contained in this press release include, but are not limited to, the parties potential inability to consummate the proposed transaction, including as a result of a failure to satisfy closing conditions to the proposed transactions; risks that QPhoton will not be integrated successfully; failure to realize anticipated benefits of the combined operations; potential litigation relating to the proposed transaction and disruptions from the proposed transaction that could harm the Companys or QPhotons business; ability to retain key personnel; the potential impact of announcement or consummation of the proposed transaction on relationships with third parties, including customers, employees and competitors; conditions in the capital markets; and those risks described in Item 1A in the Companys Annual Report on Form 10-K for the year ended December 31, 2021, which is expressly incorporated herein by reference, and other factors as may periodically be described in the Companys filings with the SEC. The Company undertakes no obligation to update or revise forward-looking statements to reflect changed conditions.

Qatalyst is the trademark of Quantum Computing Inc. All other trademarks are the property of their respective owners.

Company Contact:Robert Liscouski, CEOQuantum Computing, Inc.+1 (703) 436-2161Email Contact

Investor Relations Contact:Ron Both or Grant StudeCMA Investor Relations+1 (949) 432-7566Email Contact

Media Relations Contact:Seth MenackerFusion Public Relations+1 (201) 638-7561qci@fusionpr.com

Continued here:
Quantum Computing Inc. Unveils Software Breakthrough That Amplifies Quantum Computer Processing Power By Up to 20x - Yahoo Finance

Now Is the Time to Plan for Post-Quantum Cryptography – DARKReading

RSA CONFERENCE 2022 Even the most future-facing panels at this year's RSA Conference are grounded in the lessons of the past. At the post-quantum cryptography keynote "Wells Fargo PQC Program: The Five Ws," the moderator evoked the upheaval from RSAC 1999 when a team from Electronic Frontier Foundation and Distributed.net broke the Data Encryption Standard (DES) in less than a day.

"We're trying to avoid the scramble" when classical cryptography techniques like elliptic curve and the RSA algorithm inevitably fall to quantum decrypting, said Sam Phillips, chief architect for information security architecture at Wells Fargo. And he set up the high stakes encryption battles often have: "Where were all the DES implemented? Hint: ATM machines."

"We had to set up teams to see where all we were using[was DES] and then establish the migration plan based upon using a risk-based approach," Phillips said. "We're trying to avoid that by really trying to get ahead of the game and do some planning in this case."

Phillips was joined on stage by Dale Miller, chief architect of information security architecture at Wells Fargo, and Richard Toohey, technology analyst at Wells Fargo.

Toohey, a doctoral candidate at Cornell University, handled most of the technical aspects of quantum computing during the panel.

"For most problems, if you have a quantum calculator and a regular calculator, they can add numbers just as well," he explained. "There's a very small subset of problems that are classically very hard, but for a quantum computer, they can solve [them] very efficiently."

These problems are called np-hard problems.

"A lot of cryptography, specifically in asymmetric cryptography, relies on these np-hard type problems things like elliptic curve cryptography, the RSA algorithm, famously and when quantum computers are developed enough, they'll be able to brute-force their way through these," Toohey explained. "So that breaks a lot of our modern classical cryptography."

The reason why we don't have crypto-breaking quantum computers today, despite headline-making offerings from IBM and others, is because the technology to reach that level of power has not been accomplished yet.

"To become a cryptographically relevant quantum computer, a quantum computer needs to have about 1 to 10 million logical qubits, and those logical qubits all need to be made up of about 1,000 physical qubits," Toohey said. "Today, right now, the largest quantum computers are somewhere around 120 physical qubits."

He estimated that to even muster the first logical qubit will take three years, and from there it has to scale up to "a million or so logical qubits. So it's still quite a few years away."

Another technical challenge that needs solving before we get these powerful quantum computers is the cooling systems they require.

"Qubits are incredibly sensitive; most of them have to be held at very low, cryogenic temperatures," Toohey explained. "So because of that, quantum computing architecture is incredibly expensive right now."

Other problems include decoherence and error correction. The panel agreed that the combination of these issues means crypto-cracking quantum computers are eight to10 years away. But that doesn't mean we have a decade to address PQC.

The panel was named for the journalistic model of five questions that start with the letter "w," but that didn't come up until late in the audience Q&A portion.

"Sam was asking the what, the who, the why, the where, and the when," Miller said. "So I think we've covered that in our conversations here."

Most of the titular questions were somewhat vague and a matter of judgment. However, on the concept of when you should start planning for the post-quantum future, there was complete agreement: Now.

"You've got to start the process now, and you have to move yourself forward so that you are ready when a quantum computer comes along," Miller said.

Phillips concurred.

"There is not right now a quantum computer that is commercially viable, but the amount of money and effort going into the work is there to move it forward, because people recognize the benefits that are there, and we are recognizing the risk," he said. "We feel that it's an eventuality, that we don't know the exact time, and we don't know when it'll happen."

Toohey suggested beginning preparations with a crypto inventory again, now.

"Discover where you have instances of certain algorithms or certain types of cryptography, because how many people were using Log4j and had no idea because it was buried so deep?" he said. "That's a big ask, to know every type of cryptography used throughout your business with all your third parties that's not trivial. That's a lot of work, and that's going to need to be started now."

Wells Fargo has a goal to beready to run post-quantum cryptography in five uears, which Miller described as"a very aggressive goal."

"So the time to start is now," he said,"and that's one of the most important takeaways from this get-together."

Pivoting is a key marker of agility for the panel, and agility is vital for being able to react to not just quantum threats, but whatever comes next.

"The goal here should be crypto agility, where you're able to modify your algorithms fairly quickly across your enterprise and be able to counter a quantum-based attack," Miller said. "And I'm really not thinking on a day-to-day basis about when is the quantum computer going to get here. For us, it's more about laying a path and a track for quantum resiliency for the organization."

Toomey agreed about the importance of agility.

"Whether it's a quantum computer or new developments in classical computing, we don't want to be put in a position where it takes us 10 years to do any kind of cryptographic transition," he said. "We want to be able to pivot and adapt to the market as new threats come out."

Because there will be computers that can break current cryptography techniques, organizations do need to develop new encryption methods that stand up to quantum brute-force attacks. But that's only the half of it.

"Don't just focus on the algorithms," Phillips said. "Start looking at your data. What data are you transiting back and forth? And look at devaluing that data. Where do you need to have that confidential information, and what can you do to remove that from the exposure? It will help a lot not only in the crypto efforts, but in terms of who has access to the data and why they have to have access."

One open question loomed over the discussion: When would NIST announce its picks for the new standards to develop for post-quantum cryptography? The answer: Not yet. But the uncertainty is no cause for inaction, Miller said.

"So NIST will continue to work with other vendors and other companies and research groups to look at algorithms that are further out there," he said. "Our job is to be able to allow those algorithms to come into place quickly, in a very orderly manner, without disrupting business or breaking your business processes and [to] be able to keep things moving along."

Phillips agreed. "That's one of the reasons for pushing on plug and play," he said. "Because we know that the first set of algorithms that come out may not satisfy the long-term need, and we don't want to keep jumping through these hoops every time somebody goes through it."

Toohey tied the standards question back into the concept of preparing now.

"That way, when NIST finally finishes publishing their recommendations, and standards get developed in the coming years, we're ready as an industry to be able to take that and tackle it," he said."That's going back to crypto agility and this mindset that we need to be able to plug and play. We need to be able to pivot as an industry very quickly to new and developing threats."

Here is the original post:
Now Is the Time to Plan for Post-Quantum Cryptography - DARKReading

I beheld a quantum computer. It was weird and excellent. – Stuff

IBM

IBM scientist Andreas Fuhrer looks at the cryogenic refrigerator which keeps a quantum computers qubits super cold.

Peter Griffin is a freelance science and technology writer. He was the founding director of the Science Media Centre and founding editor of Sciblogs.co.nz

OPINION: You have to hand it to the likes of Niels Bohr, Werner Heisenberg and Erwin Schrdinger, scientists who were instrumental in developing the field of quantum mechanics about 100 years ago.

They had their work cut out for them trying to explain to a sceptical public the forces that dictate how the world works on the atomic and subatomic scale.

Even Albert Einstein whose own discoveries were towering reference points for these scientists could never reconcile that quantum measurements and observations are fundamentally random.

"It is this view against which my instinct revolts," he wrote in 1945.

READ MORE:* What does Google's Quantum Supremacy actually mean?* World-first experiment introducing atoms to one another may be key to next 'quantum revolution'* Quantum computer a possibility in 10 years* The ultimate geek pilgrimage* A computer 100m times faster than yours

Weve learned much about quantum mechanics since then, including how the principles of superposition and entanglement explain how information can be processed in ways computers like our laptops and smartphones cant match.

Last week I stood for the first time in front of a fully functioning quantum computer, IBMs Quantum System One, at the companys research labs in Yorktown Heights, New York.

The machine looks like a beautiful gold chandelier shrouded in a metal case that creates a vacuum in which the whole device is chilled to just above absolute zero, as cold as outer space.

The highly controlled conditions are required to eliminate interference that could prevent the quantum chip at the tip of the chandelier from doing its thing, which is to activate qubits the quantum version of the bits, the digital ones and zeros our binary computers work with.

IBM, Google, Microsoft and numerous other companies and research institutions have demonstrated how quantum computers are very good at a narrow range of computational tasks, such as simulating nature. Thats already seen them put to work modelling molecules and in the complex field of materials science.

ROBERT KITCHIN/Stuff

Stuff science columnist Peter Griffin.

Programmers are now working on computer algorithms to expand the ways in which quantum computers can be used. Cryptography experts think large quantum computers could crack existing encryption systems, which would cause a cybersecurity nightmare.

But quantum computers will need to scale up massively in power and be less prone to errors to be useful more broadly. IBM last year produced Eagle, a 127-qubit processor for its quantum computer and plans to introduce Osprey, its 433-qubit chip this year.

Eventually machines with hundreds of thousands or millions of qubits could be available for number crunching on a scale weve never seen before.

It's unlikely youll ever have a quantum computer on your desk or in your garage. Instead, IBM and its rivals rent access to their quantum computers as a cloud computing service.

Todays regular computers arent heading for the dustbin either. They are better at a wide range of tasks and can work in tandem to make quantum computers more useful.

Its unclear whether quantum computing can be properly applied to solving the big problems facing the world new antibiotics or climate change.

But the blistering pace of technical progress suggests it's a field heating up and one worth watching.

Read the original:
I beheld a quantum computer. It was weird and excellent. - Stuff

How Zapata and Andretti Motorsport Will Use Quantum Computing to Gain an Edge at the Indianapolis 500 – Quantum Computing Report

You might think that auto racing would not be a good application for quantum computing because the teams consist of grease monkeys who may know auto mechanics but wouldnt know how to leverage advanced computing. But you would be wrong.

Auto racing is a big business where there can be a very thin line between success and failure. To give you an idea of how small things can make a big difference you can look at the results of the 2015 Indianapolis 500. In that race, the difference in finishing time between first place finisher Juan Pablo Montoya and second place finisher Will Power was 104.6 milliseconds. And those 104.6 millisecond made the difference between winning a first-place prize of $2.44 million or not.

It turns out that an auto race generates a lot of data, about 1 Terabyte per car in a typical race, that if analyzed and used wisely can help give a racing team a critical edge. To that end, Zapata Computing and Andretti Motorsports formed a partnership earlier this year to work together on race analytics and see how they could use Zapatas advanced analytics, quantum techniques, and Orquestra hybrid classical/quantum data and workflow manager to win more races.

Although this work between the two companies has just started, a big event for both companies will occur this weekend with the 2022 Indianapolis 500 race. We talked with Chris Savoie, CEO of Zapata Computing, and he described three of the first use cases where they believe advanced analytics, machine learning, and quantum computing can potentially make a difference.

Tire Degradation Analysis

When you have a car going at over 200 MPH, the tires wear out very quickly. In a typical Indianapolis 500 race, the tires can be changed 5 or more times and require time wasting pit stops to accomplish. Whats more the tires have different characteristics when they are just put on and when they have been used a while. So, the racing manager has a lot of strategic variable juggle. When should the car be called in for a pit stop to change the tires, which set of tires should they put on the car, and how many tire changes should they have, and what is the current weather and track conditions? For a data analyst, this is a large optimization problem and will be one of the first areas that Zapata will work on with Andretti to create a ML model that can help guide these decisions using data collected in previous race sessions as well as data collected in real time during the race.

Fuel Savings Opportunities

Cars need to be refueled during the race. In addition, the driver has some control over the fuel consumption by the way he drives. If a racing team can find a way to minimize the number of refuelings and avoid a pit stop, it can save a lot of time. Whats more you dont want to cross the finish line with a full tank because they would be a waste. In the 2016 race, driver Alexander Rossi took a gamble and decided not to go for a final pit stop to refuel with 33 laps to go. It turns out he ran out of gas at the very end and coasted across the finish line. But he won the race because the second-place guy did decide to refuel and the extra pit stop time cost him the race. So, finding ways to improve fuel consumption and determine the best timing for refueling also turns out to be an optimization problem that may an opportunity to use machine learning and advanced analytics to find the best solution and improve race performance.

Yellow Flag Predictive Modelling

A yellow flag during the race occurs when an accident occurs or there is debris on the track. Drivers are required to reduce their speed and passing another car is prohibited. One of the impacts of this, is that the relative lead of one car over another is reduce. But it may also be a good time to go in for a pit stop since the cars arent going at full speed while the flag is on. If a racing team had a crystal ball and could predict when a yellow flag would occur, it could help them determine their best pit stop strategy. This may seem a little far-fetched but the Zapata/Andretti team will attempt to create a model for this that will be based upon conditions on the track, the status of the various cars in the cars, which particular drivers are in those cars, and other factors collected during the race. It will be interesting to us to see if they can actually create a useful model for when yellow flags may occur from this data.

From an operations standpoint, working in this environment can present some unique challenges. But it also provides learning opportunities for the Zapata team as they face real world challenges and find ways to solve them that can be used for future product enhancements and customer engagements in other areas. One of the first things to understand is the racing environment requires real time decisions and you do not want to use a quantum computer somewhere in the cloud on race day. The latencies will be too slow and you dont want to have to struggle with flaky Wi-Fi connections. So, Zapata and Andretti have set up an on-site Race Analytics Command Center as shown in the picture below.

Zapata and Andretti arent going to install a quantum computer in this trailer, but it will have a large amount of classical computing capability to help the team make real time decisions on race day. Machine learning applications are typically divided into a training session that develops the optimum coefficients for a model and an execution portion that just runs the model and provides an output based upon the previously setup coefficients. The training portion is the most computationally intensive portion of an ML model, they do not have to run in real time and is a good opportunity for leveraging quantum computing. Executing a model once it is created is not so computationally intensive and can be done on a classical processor. The team can feed in data from previous races and trial runs, create an ML model over many days or weeks, but then execute the ML model in real time on classical computers sitting in this trailer.

The collaboration between Zapata and Andretti goes much beyond leveraging quantum computing. The overall program will involve working with multiple data bases that could be resident with cloud providers, edge computing data coming in from various sensors, and managing workflows that are both classical and quantum in nature. Zapata will be using their Orquestra product to help manage all this.

This will be a long-term collaboration. Because the available quantum computers are not yet powerful enough to provide an advantage, the first implementations of this work will use quantum-inspired algorithms. However, the intent is that as the quantum processors become more powerful, these algorithms will eventually be moved for full quantum computers and allow the companies to create larger, more complex, and more accurate models to further their advantage. Andretti participates in many different types of auto racing and has many different teams. So, the two companies will have a lot of opportunities to try out and develop this capability. We also expect the companies will find additional use cases for leveraging advanced computing capabilities as they work together.

For additional information about this collaboration, a news release posted on the Zapata web site can be accessed here.

May 26, 2022

Read this article:
How Zapata and Andretti Motorsport Will Use Quantum Computing to Gain an Edge at the Indianapolis 500 - Quantum Computing Report