In the realm of quantum computing and molecular science, a new paper by Insilico Medicine, a leader in AI-driven drug discovery, is turning heads.

The researchers, in collaboration with the University of Torontos Acceleration Consortium and Foxconn Research Institute, have unveiled a novel approach that integrates quantum computing with the study of living organisms.

This fascinating work holds the promise of deepening our understanding of complex biological processes like aging and disease.

The foundation for this innovative approach was laid in May 2023 when the collaborative team published their research on quantum generative adversarial networks in generative chemistry in the American Chemical Societys Journal of Chemical Information and Modeling.

This marked a significant stride in demonstrating the potential benefits of quantum computing in this field.

The latest paper from Insilico builds upon this foundation. It offers a comprehensive view of how a fusion of AI, quantum computing, and the physics of complex systems can lead to new insights into human health.

The researchers highlight the latest advancements in physics-guided AI, emphasizing its potential in revolutionizing our understanding of biological phenomena.

AI has been instrumental in helping scientists process and analyze vast, intricate biological datasets, uncovering new disease pathways and linking aging and disease at the cellular level.

However, applying these insights to more complex interactions within the body remains a challenge.

According to the Insilico team, overcoming this hurdle requires multimodal modeling methods that can handle the complexity of scale, algorithms, and ever-growing datasets.

While we are not a quantum company, it is important to utilize capabilities to take advantage of the speed provided by the new hybrid computing solutions and hyperscalers, says co-author Alex Zhavoronkov, PhD, founder and co-CEO of Insilico Medicine.

As this computing goes mainstream, it may be possible to perform very complex biological simulations and discover personalized interventions with desired properties for a broad range of diseases and age-associated processes. We are very happy to see our research center in the UAE producing valuable insights in this area, Zhavoronkov concludes.

The paper delves into the intricate biological processes that span from cellular to organ to systemic levels, highlighting the need for simultaneous multi-scale analysis.

With the advent of projects like the 1000 Genomes Project and the UK Biobank, which have generated an unprecedented volume of biological data, the necessity for immense computing power to process and analyze this data has never been greater.

Quantum computing emerges as a game-changer in this context. Its ability to augment AI methods, thanks to the unique properties of qubits that hold values of both 0 and 1 simultaneously (unlike classical bits), provides vastly superior computing speed and capability.

This advancement is evidenced by IBMs recent developments in quantum computing, including a utility-scale quantum processor and the first modular quantum computer.

The authors advocate for a physics-guided AI approach to gain a deeper understanding of human biology.

This emerging field, combining physics-based and neural network models, is poised to unlock new dimensions of biological research.

By leveraging AI, quantum computing, and complex systems physics, scientists are better equipped to understand how interactions at smaller scales within cells, organisms, or societies give rise to emergent characteristics observable at larger scales.

In summary, this research represents a significant leap forward in computational molecular science. By harnessing the combined powers of AI and quantum computing, researchers are on the cusp of unraveling some of the most intricate mysteries of life, paving the way for revolutionary discoveries in human health and disease.

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Quantum computing can help decode the mysteries of aging and disease - Earth.com

Early quantum computing pioneer D-Wave again asserted that at least for D-Wave the commercial quantum era has begun. Speaking at its first in-person Analyst Day last week, CEO Alan Baratz touted the companys steady technical progress, assembled a few key customers to recount their D-Wave experience, and closed with a Q&A that provided details on its go-to-market approach and the costs to customers. The overall message of the day was a close reprise of Baratzs Qubit23 message last January D-Wave is open for commercial business.

Heres the Baratz pitch:

Many of you have heard me say this before, but its a very important point, D wave is absolutely unique in the quantum industry. Not only were we the first, but we are the only commercial quantum computing company. We have businesses that are either working with us today to develop applications to benefit their business operations, or they have moved those applications into production, and their businesses are benefiting today. Moreover, the quantum industries is absolutely at a watershed moment, said Baratz.

We are now at the point where quantum is transitioning from research experimentation to actual in production business support. But theres only one company that can say that and thats D-Wave because were the only company in the world that has quantum computers, hybrid solvers and quantum services that are able to support business applications in production. Everybody else in the quantum industry is still working on developing their systems. Thats a critically important point. That also means that D-Wave is the company that is single handedly building the quantum marketplace, because were the only ones that can do it.

These are broad claims, and many in the quantum industry disagree, even as widespread debate continues over when (and how) quantum computing will deliver value.

D-Wave, founded in 1999, has long championed a form of quantum computing quantum annealing (QA) that works quite differently from the gate-based approaches being pursued by the majority of quantum computer developers. The company also has a new gate development effort, but Baratz believes those systems are far from ready for everyone Ill say it again, we are at least seven years away from the gate model system being able to solve a real-world problem because theres just no evidence that a gate model system can solve a real-world problem without error correction.

The big bet D-Waves big bet is that quantum annealing, which does not require active error correction (EC), is the only current quantum option; its been shown to be effective for certain classes of problems, especially optimization. For two decades, D-Wave has been steadily improving the characteristics of its machines including coherence times and connectivity. Its systems support higher qubit counts because they dont need EC. The company has developed hybrid quantum solvers for a variety of application areas, and it now says it is verticalizing efforts around the long hanging fruit. Critically, it has a few customers using its systems for at least some production-environment jobs with broader roll-outs underway.

It also has pressure, not least from financial markets. In 2022, D-Wave went public (NYSE-QBTS) via the SPAC route, along with a handful of others, and twice faced delisting.

Theres a lot to unpack in the D-Wave journey. Is this D-Waves first-mover advantage moment, as Baratz declared, and the start of quantum annealing going mainstream while gate-based system continue development? Or something else?

Much of the material covered in the meeting wasnt new having become public over the course of the past couple of years. That said, it represents D-Waves self-view today, and while this was an Analyst Day intended to impress its audience, D-Wave has put many pieces to the QA puzzle together. Is it enough?

Before digging into a few meeting highlights (technology, use cases, go-to-market strategies and user costs) look at the three slides below (click on to enlarge) describing D-Wave position today. (Link to video of D-Waves Analyst Day)

Lets start with technology.

Unconstrained by active error correction, D-Wave systems have always had higher qubit counts. The first-gen Advantage system, now in use, has 5000 qubits. Key technology challenges have included increasing qubit connectivity, extending coherence times, and incorporating error mitigation. Advantage2, expected in 2023/24, will have 7000 qubits. By comparison, most gate based QPUs have far fewer (mostly single digits to 100ish). More qubits and connectivity mean larger, more complex problems can be mapped onto the processor. Better coherence means better answers.

Coincident with the analyst day, D-Wave announced it has calibrated a1,200+ qubit Advantage2 prototype, which will be available (Q1) in the companys Leap real-time quantum cloud service.

The new Advantage2 prototype features 1,200+ qubits and 10,000+ couplers, double the number of qubits and couplers over thepreviously released Advantage2 prototype. D-wave reported benchmarks demonstrate substantial advancements across a number of performance metrics compared to the Advantage quantum processing unit (QPU), including:

D-Wave says the new Advantage2 prototype is 20 times faster at solving spin glasses, an important family of classically hard optimization problem: Recent research has shown that compared to the Advantage system, the Advantage2 prototype grows quantum correlations twice as fast in materials simulation and shows significantly reduced errors in quantum simulation tasks. Further, it shows improved performance on constraint satisfaction problems, with the Advantage2 prototype beating the Advantage system 90% of the time.

An enhanced fabrication stack was developed to achieve the gains. Advantage2 system will mark the companys sixth-generation quantum system. Baratz noted the 1200-qubit Advantage2 prototype is already more powerful than our current 5000 qubit events. He also cited a recent Nature paper that showed while we are doing quantum annealing, we get a significant speedup over classical systems on hard optimization problems, in particular a polynomial speed up, not an exponential speed up.

The companys relatively new gate-based development program is also proceeding. D-Wave has chosen to work with fluxonium qubits and recently reported, manufactured and tested fluxonium qubits in a 2-dimensional circuit geometry. The measured coherence properties, with relaxation times in excess of 100 microseconds, are comparable to the current state-of-the-art for such qubits. In addition, the measured effective temperature of its fluxonium, 18 millikelvin, is among the best that has been reported in the scientific literature to date for superconducting qubits.

Baratz said D-Wave has been able leverage much of the technology developed for quantum annealing for its gate-based efforts, including for example, programming and readout able to achieve readout 20 times faster than anything thats ever been shown on gate model systems in the edge.

Theyre all using something called dispersive readout, which is not a great technology. We have already developed much better technology for doing that annealing, and its directly applicable to gate, and weve been able to show that, according to Baratz. The next step, he said, is to bring together the flexibility and high coherence of fluxonium qubits with the control capabilities that we developed to build a logical gate. Weve already designed the mask for those next step is to fabricate and test.

Turning quantum technology into practical solutions, deployed in a production environment, and, of course delivering sufficiently superior performance to classical systems to warrant the cost and effort is everyones goal. The projects reviewed by D-Wave customers covered a range of optimization activities are at various stages of roll-out: Pattison Food Group (E-commerce driver and delivery scheduling); Davidson Technologies (radar scheduling); IPG (tour scheduling); Vinci Energies (HVAC design).

Perhaps the furthest along is work by food products giant Pattison, presented by Lindsay Dukowski, senior manager, delivery scheduling. What began as a workforce scheduling project in 2020 was briefly paused by the Pandemic. It morphed into a successful ecommerce auto delivery scheduling application, now in use.

Of the initial project, Dukowski said, Across 13 different collective bargaining agreements, the rules to create a schedule were extremely complicated, and labor intensive, as well. So, we were looking at Workday (ERP solution), for instance, a leading application and even they couldnt solve this problem. I was actually leading that project at the time. We decided to partner with D-Wave to try to solve that problem.

Think scheduling how many cashiers you need, how many people in a bakery or the deli, and all of the scheduling rules and constraints, she said, including all the labor rules such as whos available, whos qualified to work in every department, and years of experience.

It takes between 8-to-12 hours a week per store to just complete. Once thats done, we put it into our workforce management application. Because these schedules are usually generated about three weeks in advance, theres a lot of last minute changes and edit sick time, new hires, terminations that have to be taken into consideration. All of that maintenance takes another 8-to-12 hours. If you think about 300 stores, its actually pretty expensive for us.

Pattison did a POC in a non-unionized store in July 2020 that was successful. Our leadership [said], youve proven you can solve this problem. Lets roll it out in the other stores (unionized) to see if you can actually really do this in a more complex environment.

COVIDs arrival changed the plan. You can imagine there are stores we had a lot of people calling in sick, a lot of people that werent willing to come in because they had family members that were at risk. COVID was crazy for the grocery industry, for every industry, but for grocery especially. We decided to kind of put that on pause, recalled Dukowski.

Pattison had e-commerce (order online for delivery) in about ~20-30 percent of its stores was pushing to expand that to all its stores. We decided to pivot and solve the e-commerce driver auto scheduling; so a very similar problem to coming up with the schedule at retail where youve got demand for drivers to deliver to multiple locations at the same time.

That project became QEDA Quantum Ecommerce Driver Automated scheduling. She recalls that e-commerce was in ~100 stores and 3-4 people that were manually creating these schedules every week and it took about 80 hours.

We went through the labor agreements. My team actually read through all of the documents. Then we met with the schedulers to find out the requirements. We converted those requirements to math equations, we built data pipelines to pull in all the necessary data from the source systems, converted that to an optimization code. We use the hybrid solver from D-Wave, did some code debugging and parameter tuning, outputted some schedules and then just kind of iterated the process until till it worked, Dukowski said.

The weekly manual effort for scheduling creation was reduced by 80% from 80 hours to 15. And that time is really for the maintenance and the edits that need to be made. Its difficult. We didnt try to solve that problem with this, it was just lets generate a schedule. Initially, the runtime per schedule is about two minutes, and then we generate 42 schedules each week. So, if you think about the timeline, we started in April, we did a pilot in August, and moved into production, October 2022.

I believe that at that time, we became the first the first company in North America to go live with a production system using quantum, said Dukowski.

Pattison has since returned to the workforce management application. We took the demand, we automated all of those scheduling rules, using the same project methodology and essentially the same tech stack to build a new model and pull in additional data. So, we have some new data pipelines we had to build, but leverage the work that we did with the E commerce driver scheduling, and were able to eliminate that eight to 12 hours, she said.

The scheduling challenge is one of those application areas D-Wave is currently focusing what Baratz called the low hanging fruit because the tools, hybrid solvers, and D-Wave quantum computer can effectively handle them. We are targeting manufacturing, logistics, and doubling down on key use cases such as workforce scheduling, resource allocation, and vehicle routing he said.

These projects remain non-trivial and take time, as indicated by the Pattison example. Baratz provided some detail around customer engagements.

Over the course of the last year and a half to two years since we launched our professional services organization, weve now done over 25 proofs of concept with customers. Were now at the point where they are starting to move into production [and] we expect a few more over the course of the next three months. This is a really important transition for us because of our business model. Ultimately, we want to focus on quantum computing as a service, because that allows us to build recurring revenue. And that puts us in a much more predictable revenue growth position going forward, said Baratz.

In Q&A, Baratz was asked to distinguish and contrast the overall 70 commercial customers with the ~25 POC cited earlier.

Keep in mind that not all customers [that] engage us do POC. We have a lot of customers that we affectionately call DIY customers, right? They come in, they buy in the old days of time and in new days a developer seat and then try to build the application themselves. What we know is that the customers that try to do it, themselves have a much lower probability of success than when they engage us in a POC, said Baratz.

Professional services helps them to figure out how to properly leverage the quantum computer, how to properly map the application, but as we go through it we can help them understand how to do so it doesnt always have to be us, he said. A lot of those 70 customers are those DIY customers. One of the things we are focused on is going back to them, and trying to move them to a POC, so that we can help them be more successful.

The standard pricing for proof of concept is about $350,000, said Baratz. We also have a $70,000, demonstrator engagement thats a one month engagement with a demonstration thats really quick and dirty to kind of feel out the solution to your problem. You cant run it because not linked to your environment. But you give us some data. We figure out how to solve a problem on your data, leveraging quantum hybrid solvers, said Baratz.

Moving into production is a deeper engagement. If the customer wants our help in trying to move to production, thats typically a custom agreement.

D-Wave has two production offerings.

Asked who owns the application developed with POCs and if D-Wave is able add newly-developed applications to its library, Baratz said, Wed love to have them, but our customers would not sometimes. Basically, what weve done is weve defined an interface, and typically what we say is anything thats developed below that interface we own. For example, if we make a change to a hybrid solver to support your application we own that; anything above that interface you own so typically, if the application is owned by our customers. But not always, sometimes weve been able to retain that.

As outlined by Baratz, D-Wave clearly has big ambitions and believes the timing is right. He notes that quantum annealing, sometimes disparaged in the past, has recently got a boost from government with favorable language in recent National Defense Authorization Act Weve already started getting calls from various defense agencies saying we need to learn more. The last call we got was from the army engineering research lab, he said.

Stay tuned.

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Eyes on the Quantum Prize D-Wave Says its Time is Now - HPCwire

In the world of quantum computing, the spotlight often lands on the hardware: qubits, superconducting circuits, and the like. But its time to shift our focus to the unsung hero of this tale the quantum software, the silent maestro orchestrating the symphony of qubits. From turning abstract quantum algorithms into executable code to optimizing circuit designs, quantum software plays a pivotal role.

Here, well explore the foundations of quantum programming, draw comparisons to classical computing, delve into the role of quantum languages, and forecast the transformational impact of this nascent technology. Welcome to a beginners guide to quantum software a journey to the heart of quantum computing.

At its heart, the world of quantum computing contrasts starkly with that of classical computing. The differences extend beyond hardware to the very core of programming. Lets illuminate some of the primary distinctions that delineate these parallel universes of computing.

Classical computers, the type most of us use daily, operate on binary data. This means they process information in bits, which are either in a state of 0 or 1. Classical programs, thus, revolve around manipulating these bits using logical operations.

Quantum computers, however, function quite differently. They leverage the quirks of quantum physics to process information via qubits. Unlike bits, a qubit can exist in multiple states simultaneously, thanks to a phenomenon called superposition. Additionally, qubits can also be entangled, meaning the state of one qubit can instantaneously affect the state of another, no matter the distance between them.

Therefore, programming a quantum computer necessitates a new approach, new logic, and an entirely new set of programming languages. Quantum software developers do not merely instruct a sequence of operations; they choreograph a dance of qubits, harnessing the peculiar properties of quantum physics to solve complex problems. The beauty of quantum programming lies in its ability to weave a ballet of superpositions and entanglements to achieve solutions exponentially faster than classical computing.

Quantum computing does not replace classical computing. Instead, it complements it, addressing problems that are currently unsolvable with classical computers due to the type of calculation and its complexity. Quantum software, therefore, requires a firm understanding of both classical and quantum principles to effectively leverage the strengths of each and navigate their respective challenges.

Quantum programming demands a unique set of terms to address the building blocks of a quantum program. These terms help us to describe and navigate the multi-dimensional universe of quantum computation. Here, we highlight three of these terms: quantum gates, quantum circuits, and quantum algorithms.

Quantum Gates: Much like classical computers use logical gates (AND, OR, NOT), quantum computers operate with quantum gates. But unlike their classical counterparts, quantum gates are reversible and deal with probabilities. They manipulate the state of qubits to perform quantum operations. A few examples include the Pauli-X, Pauli-Y, Pauli-Z, Hadamard, and CNOT gates.

Quantum Circuits: A sequence of quantum gates forms a quantum circuit. The quantum circuit defines the transformations that the qubits undergo to solve a given problem. However, the circuits behavior is inherently probabilistic due to the nature of quantum physics.

Quantum Algorithms: Quantum algorithms are sequences of quantum circuits designed to perform a specific task or solve a specific problem, much like a sequence of instructions forms a classical algorithm. Some popular quantum algorithms include Shors algorithm for factoring large numbers, and Grovers algorithm for searching unsorted databases. Quantum algorithms exploit the phenomena of superposition and entanglement to outperform classical algorithms for certain problem types.

In the realm of quantum programming, were essentially designing a choreographed sequence that manipulates qubits through these quantum gates, forming quantum circuits to execute quantum algorithms. All this, to solve problems that classical machines find insurmountable.

The world of quantum programming is as diverse as the set of problems it aims to solve. Various quantum programming languages and software platforms have emerged to address different needs, each with its unique approach and strengths. Here, we introduce you to this rich landscape.

Quantum Programming Languages: Just as classical computing has its C++, Python, and Java, quantum computing too has developed its languages. For example, Q# from Microsoft and Qiskit from IBM are two of the most popular quantum programming languages today. They allow you to define and manipulate quantum states, apply quantum gates, and measure the results.

Here we can see qiskit code that creates a quantum register with two qubits and applies a Hadamard gate to the first qubit and a CNOT gate to the two qubits. The code then measures the two qubits.

Software Platforms: Aside from standalone programming languages, there are software platforms designed to aid in quantum development. For instance, our platform at CLASSIQ provides an intuitive, visual way to design quantum circuits and algorithms. It is this high-level abstraction that allows quantum developers, beginners, and experts alike, to harness the power of quantum computing without getting bogged down in the low-level details of gate definitions.

Remember, each tool and language has its strengths, and the choice often depends on the problem youre tackling. Its about choosing the right tool for the right job, much like in the world of classical computing.

While programming a quantum computer can initially seem daunting, a high-level perspective simplifies the task into a series of logical steps. Heres an overview of the general process:

Problem Formulation: The first step in quantum programming is defining the problem you want to solve. This might be optimizing a financial portfolio, simulating a chemical reaction, or breaking an encryption code. Its crucial to understand that not all problems are suited for quantum solutions. Some tasks may be more efficiently handled by classical computers. Therefore, selecting the right kind of problem is a pivotal decision.

Algorithm Selection: Once you have defined the problem, the next step is to choose a quantum algorithm that can solve it. There is a growing library of quantum algorithms, each designed to address a particular type of problem. Some algorithms are well-suited for optimization tasks, while others are designed for simulation or machine learning.

Implementation: With the problem and algorithm in hand, you can now proceed to implementation. This is where quantum programming languages and platforms come into play. You translate the chosen algorithm into quantum code using your selected language or platform. This is often the most technical part of the process, and it can involve complex tasks like designing quantum circuits and managing quantum states.

Execution and Analysis: Finally, you execute your quantum program on a quantum computer or simulator and analyze the results. Since quantum computing is probabilistic, you may need to run your program multiple times to achieve a statistically significant result. The analysis often involves interpreting the quantum results in the context of your original problem.

Just like learning to program in a classical sense, the path to becoming proficient in quantum programming involves practice, patience, and a whole lot of curiosity.

The implications of quantum computing are broad and promising. As we refine our abilities to harness and manipulate quantum phenomena, well witness quantum computers unlocking solutions to some of the worlds most complex and currently unsolvable problems.

Innovation in Multiple Industries: Quantum computing has the potential to revolutionize various industries. Pharmaceutical companies, for example, could use quantum systems to simulate and analyze complex molecular structures, leading to new drug discoveries. The financial sector could leverage quantum algorithms for better risk assessment, portfolio optimization, and fraud detection.

Improved Data Security: The prospect of quantum computers breaking current encryption methods is a cause for concern, yet it also presents an opportunity. As we advance in quantum computing, well simultaneously develop quantum-resistant encryption techniques, creating a new era of data security.

Scientific Discovery: Quantum computing promises to supercharge scientific discovery. In fields such as material science, quantum simulations can facilitate the discovery of new materials with desired properties. In climate science, it could offer more accurate climate predictions by better modeling complex systems.

While these exciting possibilities lie on the horizon, its important to remember that the quantum computing journey has just begun. Its a field ripe for exploration and innovation.

As we transition from theory to practice, from abstraction to application, quantum programming will play an increasingly central role. By learning the principles of quantum programming today, youre not only preparing for a quantum-powered future but actively participating in its creation.

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Mastering the quantum code: A primer on quantum software - SDTimes.com

Q-Day is when a quantum computer so powerful is built it could break the public encryption systems. How concerned should we be?

There may come a day known as Q-Day, which will shatter global security as we know it.

It could be in a few years from now, or in 10 years or more. But scientists, mathematicians, and governments are not waiting idly by for the quantum threat to happen.

Q-Day is when a quantum computer so powerful is built, it could break the public encryption systems that protect our online conversations, bank accounts, and most vital infrastructure, wreaking havoc on governments and businesses.

How this digital doomsday would happen comes down to simple maths.

Since the beginning of the Internet, cryptography has protected our online data and conversations by hiding or coding information that only the person receiving the message can read on traditional computers.

In the 1970s, mathematicians built encryption methods that consisted of numbers hundreds of digits long. The difficulty of mathematical problems was such that it could take at hundreds of years to solve if using the right parameter size and numbers.

To break the encryption, the numbers need to be split into their prime factors, but this could take hundreds if not thousands of years with traditional computers.

The threat of codes being cracked was therefore not a big worry.

That was until 1994 when the American mathematician Peter Shor showed how it could be done with an algorithm using a then hypothetical quantum computer that could split large numbers into their factors much quicker than a traditional computer.

The quantum threat was still not a significant concern back then but it started to become an issue four years later when the first quantum computer was built.

Though that quantum computer - and those currently being built - are still not powerful enough to use Shors algorithm to decrypt the numbers, in 2015, intelligence agencies determined that the advancement in quantum computing is happening at such a speed that it poses a threat to cyber security.

At the moment, qubits, the processing units of quantum computers, are not stable for long enough to decrypt large amounts of data.

But tech companies such as IBM and Google have slowly but steadily started making progress in building machines strong enough to deliver the benefits of quantum, which include pharmaceutical research, subatomic physics, and logistics.

Its a matter of time and it's a matter of how long does it take until we have a large quantum computer to go, Dr Jan Goetz, CEO and co-founder of IQM Quantum Computers, a start-up that builds quantum computers, told Euronews Next.

If it takes 30 years to build a strong enough computer, there would be less reason to panic as most of the encrypted data might no longer be relevant.

But if someone comes up with a very clever idea and can already, do the code-breaking in 3 to 5 years, the whole situation also looks different, Goetz said.

Individuals should not be concerned by Q-Day as there are probably few people who have data that is very sensitive and will still be relevant in years to come.

Goetz said once the new technology comes, encryption codes will be updated on all computers and phones and you should not be too concerned about this because the industry will take care of this.

But governments, organisations, and businesses should be concerned by the quantum threat.

There is a concept called store now, decrypt later. It means someone could be storing the data and waiting for a quantum computer strong enough to come along and decrypt it.

Governments in particular are harvesting data from the Internet, said Dr Ali El Kaafarani, founder and CEO of quantum-safe cryptography company PQShield.

They are storing data that they can't access or read at the moment, but they can keep them there until the cryptography layer becomes weaker until they know of a way to attack it and then they break it and they read those communications, he told Euronews Next.

Governments are not standing by for that to happen and the cryptographic community are building encryption methods that can withstand the quantum threat, known as post-quantum cryptography (PQC).

This year, sometime between May and June, the final standardisation of PQC will be released by the US National Institute of Standards and Technology.

This will be a game-changer as it will be on the market for all industries.

The US legislation has mandated that the timeline to change to PQC will be from 2025 until 2033, by which time the cyber secure supply chain will have to have transitioned to using PQC by default.

In 2025, web browsers and software updates will have to become post-quantum secure by default if they are sold to the US, said El Kaafarani.

This is why some companies, such as Google Chrome and Cloudflare, have already started using PQC.

The USs PQC standards are international standards, but every country has their own guidelines governments do collaborate.

The US, UK, French government, German, and Dutch governments, among others, have all weighed in and produced whitepapers and guidelines for the industry to push them to start the transition phase to post-quantum cryptography as they understand that it is a process that will take time.

Governments take care of standardising the algorithms so that we all speak the same language, said El Kaafarani, but it is the cryptographic community that comes up with the new encryption methods that are not vulnerable against quantum computers.

Most of the cryptographic standards are developed in Europe by European cryptographers, he added, whose UK-based company had four encryption methods selected to be in the USs PQC standards.

Once developed, the encryption methods are ruthlessly scrutinised by the wider cryptographic community, governments, and everyone else who is interested in cracking the encryption methods.

Some get broken along the way. And that's the whole point of the process, is to root out the weak ones and keep them the strong ones, said El Kaafarani.

But there is no perfect encryption method or security method that can ensure that everything will stay secure forever.

Therefore cryptography is naturally an evolving field and that's why we need to keep ahead and keep an eye on how things are evolving, he said.

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What is the quantum threat and what has simple maths got to do with protecting global security? - Euronews

Chinese authorities have reiterated the need for technological breakthroughs in a range of hi-tech areas, including graphics processing units (GPUs), quantum computing, humanoid robots and brain-computer interfaces, in Beijings latest effort to seek control of the industries of the future.

A document issued on Monday by the Ministry of Industry and Information Technology, the Ministry of Science and Technology, the Chinese Academy of Sciences and other departments, urges the country to grasp the opportunities of a new round of scientific and technological revolution at a time when the US is doubling down on a small yard, high fence approach to block Chinas access to key technologies.

The US has been ramping up its tech pressure on China. As a result of Washingtons October update of export restrictions for advanced chips, Nvidia is unable to sell its cutting-edge GPUs including some tailor-made for China to comply with previous regulations to the country.

Strong China demand for chip tools bolsters revenue at Lam Research and ASML

The Biden administration will require such firms to reveal foreign customer names and IP addresses, and they will need to devise a budget for collecting those details and report any suspicious activity, according to a draft rule published on Sunday.

The Chinese government is pushing a whole-of-the-nation approach to focus resources on breakthroughs in designated areas. The latest policy document identifies GPUs that can help train large language models and robots that can be used in smart manufacturing and household services.

It also mentions brain-computer interfaces, which Tesla founder Elon Musk has been developing with Neuralink, and which can be applied to medical treatments, autonomous-driving and virtual reality.

The document sets a target of achieving breakthroughs in at least 100 core cutting-edge technologies by 2025 and to become a global leader in certain areas by 2027, although it does not lay down the criteria for assessing progress.

The authorities also promise that China would actively participate in the global division of labour and cooperation and deeply integrate into the global innovation network, adding that the nation encouraged multinational corporations and foreign academic institutes to set up research centres in China.

In terms of industries, China will focus on future manufacturing, future information, future materials, future energy, future space and future health.

In recent years, Beijing has repeatedly urged scientists and companies to achieve self-sufficiency in semiconductor supplies. China aims to produce 70 per cent of the chips it uses by 2025.

The new guideline comes hot on the heels of the annual tone-setting central economic work conference in December, when Chinas top leaders set developing industries of the future as a key mission for the year ahead.

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Beijing urges breakthroughs in chips and quantum computing to command future - South China Morning Post

Unraveling the Mysteries and Potentials of Quantum Computing in Modern Tech 10 min read

As we stand on the brink of another technological revolution, quantum computing continues to fascinate and perplex minds around the globe. The concept, which once seemed like nothing more than a far-fetched theory cut from the cloth of a science fiction novel, is metamorphosing rapidly from hypothesis to reality. As we delve into this discussion on quantum computing, its essential to first set the stage by understanding the basics and appreciating its potential to transform various sectors of human activity.

Traditionally, classical computers utilize a binary system of bits that represent either a 0 or a 1. These bits are the fundamental building blocks of any computational task we perform. They form the basis of any information processed or stored on our digital devices, from the words we type to the intricate graphic designs we formulate. This classical form of computing has served as the backbone of technology for the better part of a century. It provided us the power to put man on the moon, map out the human genome, and create the very Internet youre using right now.

Yet, computer scientists and physicists worldwide identified an impending limit to the capabilities of classical computing. As problems grow increasingly complex, so does the requisite number of bits needed to compute them. This predicament birthed the concept, development, and eventual implementation of quantum computing the next significant leap in technological advancement.

Quantum computing hinges on quantum bits known as qubits. Unlike classical bits, a qubit doesnt limit itself to a state of 0 or 1; instead, it can exist in both states simultaneously, thanks to a quantum phenomenon known as superposition. Furthermore, qubits have another quantum property called entanglement, allowing them to be interconnected despite the distance between them. This quantum superposition and entanglement afford quantum computers their extraordinary computational power and parallelism.

Read more:

Decoding Quantum Computing: The Next Technological Leap | by Stern Alexander | Jan, 2024 - Medium

Quantum computers have just started to enter the mainstream awareness. Although the shift from classical to quantum computers is still ongoing and the technology experimental, the potential consequences could be far-reaching once we successfully harness the technology to societys benefit. That puts the spotlight on quantum innovation stocks leading the way forward.

Note that these quantum innovation stocks are approaching the idea and unique problems of quantum computing differently. Some are taking a high-risk, experimental approach that delves deep into the unexplored regions of physics and engineering, while others are taking the more conservative track one thats better understood.

In this article, I present three companies considered quantum innovation stocks and detail their approaches and progress to get their respective quantum systems online and commercialized. Here are the companies to consider.

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IBM (NYSE:IBM) has been a leader in quantum computing research for years. It is one of the first companies to supply customers with cloud-based quantum computing systems, and the company recently announced it was broadening its hardware offerings, too.

The company recently announced plans to install an IBM Quantum Systems Two processor at KQCs facility in Busan, Korea, by 2028. The processor is expected to be part of the IBM Flamingo family, featuring 156 qubits per module and support for up to 7 modules.

The big picture is that this reportedly attracted the attention of blue-chip clients in the Korean financial, bio-healthcare and pharmaceutical sectors. Those sectors could be heavy experimental users of quantum machines.

Quantum computers are exponentially more powerful than classical computers, and their commercialization could lead to crucial scientific developments and breakthroughs presently unreachable.

Trading at just 24.6 times earnings, IBM could be seen as undervalued in light of its progress in quantum computing.

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Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) has made significant strides in quantum computing. The company claimed to have achieved quantum supremacy in 2019. Since then, it has worked tirelessly to improve the stability and power of its quantum systems.

The company claims to be leading the quantum computing arms race, which it is apparently demonstrating by reducing the error rates of its quantum system. Last year, Googles 3rd generation Sycamore processor was reported to typically experience error rates between 1 in 10,000 to 1 in 100.

The above progress marks the second step in Googles roadmap to building an error-corrected quantum computer, and its progress seems to be accelerating.

I think quantum as an additional growth tailwind makes Alphabet a strong buy. In the short term, analysts expect its EPS to surge 16.36% in FY2024, so this may give investors something more immediate while they wait for the quantum computing market to hit its full stride.

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Microsoft (NASDAQ:MSFT) is another tech behemoth with substantial interest in quantum technologies.

MSFT, in my opinion, is one of the better stocks positioned to take advantage of this computing development. Thats because its one of the few companies to release its development toolkit Q#.

That is a highly underappreciated feature and seems to be unique to Microsoft. Q# is the programming language developers will use to develop sophisticated quantum algorithms to power applications. MSFT is already courting developers to learn and utilize this language, which interfaces with Microsofts cloud service, Azure.

Hypothetically, suppose Q# gains widespread acceptance amongst developers. That would be a significant competitive advantage and moat for MSFT to lean on due to the time investment of having to switch to a competing language and the first-mover advantage it presents for MSFT.

Q# could very well become the .NET for quantum applications, a language that needs highly specialized developers to work in the field.

Microsoft has experience building these types of ecosystems before, and I believe its capable of fostering a similar one with Q#. Its a possibility that investors should keep in mind.

On the date of publication, Matthew Farley did not hold (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

Matthew started writing coverage of the financial markets during the crypto boom of 2017 and was also a team member of several fintech startups. He then started writing about Australian and U.S. equities for various publications. His work has appeared in MarketBeat, FXStreet, Cryptoslate, Seeking Alpha, and the New Scientist magazine, among others.

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3 Stocks at the Forefront of Quantum Innovation - InvestorPlace

29Jan2024

UK-funded 'LYRA' project aims to deliver a quantum networking unit for future data centers.

University of Cambridge spin out Nu Quantum is collaborating with telecommunications equipment giant Cisco to advance quantum networking technology.

The two firms are working on a UK Research and Innovation (UKRI)-funded research project called LYRA that will aim to deliver a world-first, modular, 19-inch rack-mounted and scalable quantum data center prototype - with Cisco as a prospective future end user.

Modular architecture Running for 18 months, the LYRA project began in October 2023 and is valued at 2.3million, with other collaborators involved.

Nu Quantums VP of product management Ed Wood says that Nu Quantum will be delivering a control module comprising rack mount control electronics, and an optical module featuring discrete single-photon detectors.

The combination of the two modules will form a complete 'Quantum Networking Unit', or QNU.

This modular architecture allows in-field upgrades to support different quantum computer modalities and alternative wavelengths, announced the two companies.

The solution also incorporates a new high-precision timing-architecture and digital control bus, allowing the system to easily scale to support a large cluster of quantum-compute nodes.

Under the collaboration, Cisco says it intends to contribute to key system requirements and help to evaluate final deliverables.

Out of the lab Carmen Palacios, the co-founder and CEO of Nu Quantum, said in a joint release: We are honored to be awarded the contract from UK SBRI to pilot the first prototype of a quantum data center in the world, and to have an amazing partner like Cisco.

"LYRA takes the cornerstone quantum networking units from [the] optical bench to a deployable, prototype-product, capable of supporting test-bed integration with trapped-ion qubits and software stacks.

"The LYRA QNU is designed for future support of different qubit modalities and is a huge step forward in bringing quantum out of the lab and into real world use.

The optical module is wavelength-specific, typically matching the native emission wavelength of the ion or atom used as a communications qubit. This is required as wavelength conversion is to be avoided where possible, Wood explained.

It is a lossy process that will damage the overall performance of the system. But the modular nature of the system means that the control module can be retained and a new optical module at a new wavelength installed.

Although interfacing to the qubit is beyond the scope of LYRA - the project only requires presentation of the photons from the compute nodes into fiber - the distance of the quantum links will ultimately relate to the wavelength of the photons.

Wood says that tens of meters should be possible for any wavelength. LYRA is very specifically about use inside a datacenter (highest rate and fidelities), not long-range inter-datacenter connections, he added.

Peter Shearman, Ciscos head of co-innovation, stated: It is increasingly accepted that to reach its potential quantum networking will be needed to scale quantum computing to a fault-tolerant era.

"We are delighted to partner with Nu Quantum to accelerate this journey towards a modular, qubit-agnostic and data center-optimised future.

Link:

Cisco and Nu Quantum collaborate on quantum networking - Optics.org

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