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Quantum computing could reshape how we solve complex problems and process sums of data previously thought impossible to handle.

What could take today's computers thousands of years to solve, quantum computers could potentially calculate in seconds.

This is possible through exploiting the unique capabilities of quantum particles (or qubits) to be able to be in two places at once, and communicate mysteriously with each other even if they are millions of miles apart.

Everything from producing more efficient engines to simulating chemical reactions for developing new medicine, more powerful computing could lead to a plethora of innovation breakthroughs across the scientific disciplines and technology.

As promising as this sounds, building practical quantum computers has been tricky for engineers. Getting qubits to move between quantum chips fast and accurately has always been a major obstacle.

In February, researchers from the University of Sussex in the United Kingdom announced a breakthrough, after managing to solve this problem by cleverly using electrical fields. Quantum information was transferred between chips at record speed with an accuracy of over 99 percent.

By demonstrating that two quantum computing chips can be connected opens the way to scalability, as it means chips can be linked together, like a jigsaw, to create powerful processors.

Proving that this is possible is a major step forward in building machines that can perform functional computations using the technology.

Companies such as Google and IBM have been attempting to engineer simple quantum computers for decades now, at a slow pace. Transferring information between chips has proven difficult, especially when trying to transfer data from one point to another fast and reliably without inducing errors.

Simple quantum computations can be performed in laboratory settings, but in the real world such technology will need to operate in imperfect and unpredictable environments.

Anything from fluctuations in voltage to stray electromagnetic fields from other surrounding devices could all throw the delicate balance of quantum particles out of balance.

When dealing in the realm of the subatomic, delicacy is key, and so breakthroughs such as these could soon lead to further understandings in tapping into quantum processing technology.

Many challenges remain before quantum computing promises to unlock more secrets of reality for scientists.

Quantum computers need to be kept at an extremely cold temperature of absolute zero to minimize interference, which can cause issues when they enter mainstream research facilities. Keeping conditions stable enough for subatomic particles to work their magic is extremely challenging, and the technology is still very much in its early stages.

Slow progress is being made, and however primitive their current state is, their future potential is a worthy incentive.

When the first transistor for traditional modern computing was made in 1947, nobody could predict the impact it would have in the decades to come, with the use of smartphones and laptops just over half a century later.

The belief that quantum computing will also lead to disruptive technologies in the near future still motivates scientists to keep pushing forward. How long it may take to reach this stage, however, is something nobody is certain about.

Predicting future technologies is always difficult, and many technologies go through bursts of advancement and stagnation.

Progress in battery energy storage for example, has remained relatively stuck for many years now, which has in turn held back many other areas of innovation.

Our understanding in genetics and gene editing however, has undergone a renaissance in the last ten years, with new stem cell treatments for cancer such as Car-T therapies now available that would have been impossible even 15 years ago.

The hope is that quantum computing will follow the lead of the latter, and offer us new insights into how we can further innovation across scientific disciplines.

Barry He is a London-based columnist for China Daily.

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Quantum computing as a service (QCaaS) makes it possible for users to access qubit-enabled information processing architecture over cloud services. Qubits use real-world physics to tackle problems that are hard or even impossible to solve using the classical bits found in conventional computing machines. But when it comes to finding solutions for complex route planning tasks, users may want to consider an alternative to quantum computing. And that alternative, if you missed the biocomputing boom that occurred a decade or so ago, could come as quite a surprise.

Todays quantum processors are dubbed noisy intermediate-scale quantum (NISQ) technology. The endgame is to create fault-tolerant quantum devices featuring a million or more physical qubits, which can be turned into logical qubits using error correction methods. Quantum computing states can be extremely fragile and sensitive to their surroundings. And today, developers have to work hard to support measurements involving just a few hundred qubits, let alone millions.

Early success stories include the use of quantum computers to solve supply chain and logistics problems. But the technology comes at a price and has collectively required billions of dollars to develop. However, it turns out that nature has been busy, too, developing organisms with biocomputing properties. And one of its brightest stars can be found in the forest, which goes by the Latin name Physarum polycephalum, also commonly known as slime mould.

Visible with the naked eye, the bright yellow-coloured, single-celled organism adapts its growth based on surrounding conditions. Slime mould is attracted by nutrients such as oat flakes, deterred by repellents such as salt, and capable of avoiding hazards. Dubbed wetware, Physarum polycephalum combines hardware and software capabilities. And, to the delight of researchers, the biomaterial can be used to solve mazes and determine the shortest path between nodes in a network a notoriously difficult problem for classical computers to answer efficiently.

The ease of culturing and experimenting with Physarum makes this slime mould an ideal substrate for real-world implementations of unconventional sensing and computing devices, writes Andrew Adamatzky, director of the Unconventional Computing Laboratory within the Department of Computer Science at UWE. In the last decade, Physarum has became a Swiss army knife of unconventional computing: give the slime mould a problem and it will solve it.

And if you doubt the ability of slime mould to offer an extremely affordable and resource-efficient biocomputing alternative to quantum computing, its worth checking out some of the organisms achievements in the lab. Adamatzky and his colleagues have found particular success in allowing the mould to explore miniature replica terrains, highlighting regions of interest with nutrients that set growth parameters for the living network.

The 3D landscapes formed in Nylon sit above petri dishes of water, which make low areas more desirable for the mould due to the higher humidity. And the conditions mean that the organism spreads out its protoplasmic tubes in a way that mimics the growth of transport networks for example, by routing around mountainous areas. Researchers have shown how slime mould can reproduce the route of Germanys longest autobahn and giant road networks across the US; motorways in the Netherlands, Belgium, France and the UK; and even the Tokyo railway system.

Slime moulds ability to solve complex route planning, points towards the biocomputing material as being an alternative to quantum computing. The issue with route planning is that problems become exponentially harder for conventional computers to solve with each node added to the network. But both quantum computers and organisms such as Physarum polycephalum are capable of selecting the optimal (or at least close to optimal) path in linear time, although only slime mould is able to achieve the feat at such an incredibly low price point. And its remarkable capabilities dont just stop there.

In an extremely clever experiment, scientists demonstrated the capacity of slime mould to anticipate events. Researchers exposed the organism to regular bursts of cold air blown using a fan, which paused its growth. And the team noticed that over time the mould became used to the timings and paused its growth in anticipation even when the fan wasnt activated. Its often said that quantum computers exhibit spooky behaviour thanks to the physics of entangled qubits, but slime mould appears to have some eerie properties of its own.

Today, analysts are using digital models of slime mould to translate its ability to form efficient networks across a range of applications, including optimizing the parameters of photovoltaics. But the amoebas physical properties turn out to be useful as well. Adamatsky and his team have shown how slime mould can be integrated with electrodes to produce wires that have self-healing properties. There appears to be no end to the appeal of this organism, which is even the subject of a feature-length cinema release named The creeping garden.

If you have a few oat flakes to hand, a petri dish and access to a 3D printer to create a terrain, you could be well on the way to exploring whether biocomputers really are an alternative to quantum computers.

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Biocomputers - an alternative to quantum computing? - TechHQ

Quantum computing uses quantum mechanics to perform operations. Quantum mechanics is a physics theory that describes the physical environment at an atomic and subatomic scale, compared to traditional physics, which looks at the macroscopic scale.

Bits denote data in classical computing. These bits are two-state, the familiar 1 or 0. With quantum computing, quantum bits qubits measure computing power. These exist in multiple states at the same time, which can include combining 0 and 1 simultaneously.

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The benefits of this new computing technology include storing massive amounts of information in fewer computers while using less energy. And, by operating outside the traditional laws of physics, quantum computers can offer processing speeds millions of times faster than traditional computers.

In 2019, for example, Googles latest quantum computer performed a calculation in four minutes. The worlds most powerful supercomputer at the time would have needed 10,000 years to finish that same calculation. With 300 qubits, a quantum computers calculations at a given time are greater than the atoms in the universe.

The speed of quantum computers brings many use cases, including faster and smarter artificial intelligence (AI) platforms, advanced pharmaceutical modeling, more accurate weather predictions and the creation of new materials.

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Research firms like Contrive Datum Insights see massive quantum computing market growth. The company projects a compound annual growth rate of 36.89% from 2023 to 2030, with the market reaching $125 billion annually. Where there is that kind of growth and money involved, startups are sure to follow. With quantum computing still in the early stages, startups are tackling multiple fronts, including different computer production methods, advanced quantum algorithms and other innovations.

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Here are some of the quantum computing startups making noise in the space:

Maryland-based quantum computing hardware and software firm IonQ Inc. (NYSE: IONQ). The company partners with various firms like Hyundai Motor Co. to create better machine learning algorithms to improve safety and bring about self-driving automobiles. Hyundai is also leveraging IonQ to study lithium chemistry and find new reactive solutions for future electric vehicles (EVs).

PSIQuantum is a company developing a method of quantum computing that uses photos that represent qubits. The startup is on the CB Insights list of unicorn companies with a current valuation of $3.15 billion as of March 10. The firm completed a $450 million investment round in the summer of 2021 and continues toward its stated goal of developing a 1 million qubit computer.

French startup PASQAL offers quantum computers built with 2D and 3D arrays of ordered neutral atoms, enabling its clients to solve challenging problems. These include improving weather forecasting, boosting auto aerodynamics for greater efficiency and finding relationships between chemical compounds and biological activity for the healthcare industry.

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Established technology giants are also pushing forward quantum computing. IBM remains at the forefront. In November 2022, the company announced the creation of a 430-qubit machine named Osprey, which has the largest qubit count of any processor. IBMs breakthroughs in quantum computing mirror the trajectory of innovation for traditional computers as processing speed increased year over year.

Amazon Inc. Braket is the companys managed quantum computing service and part of its overall growth strategy with Amazon Web Services (AWS). Bracket offers users a place to build, test and run quantum algorithms. It provides them with access to different types of quantum hardware, encourages software development through the Braket SDK and to create open-source software.

Microsoft Corp., Alphabet Inc.s Google, Intel Corp. and Nvidia Corp. also offer quantum computing solutions and investment. As the biggest tech firms increase participation in quantum computing, more startups should become acquisition and merger targets as the market moves toward consolidation.

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Is 2023 The Year Of Quantum Computing Startups And A 1 Million Qubit Machine? - Yahoo Finance

Quantum computers can solve highly complex problems faster than any of its predecessors. We are currently in a period of a quantum revolution. Many organizations are currently investing in the quantum computer industry, and it is predicted that the quantum computing market may increase by 500% by 2028.

Due to their powerful computing capabilities, the Cloud Security Alliance (CSA) has estimated that by April 2030, RSA, Diffie-Hellman (DH), and Elliptic-Curve Cryptography (ECC) algorithms will become vulnerable to quantum attacks. This makes many organizations vulnerable to harvest now, decrypt later (HNDL) attacks, where attackers harvest data from organizations to decrypt when quantum computing reaches its maturity and the cryptographic algorithms become obsolete. In a new Deloitte Poll, 50.2% of the respondents believe that their organizations are at risk for HNDL attacks.

In quantum computing, the basic unit is qubits (quantum bits), but, more than the classical computing bits which exist in 0 or 1 states, qubits can exist in 0, 1, or in both combinations. Through manipulation of the information in the qubits, high-quality solutions can be provided for difficult problems. The IBM report on security in the quantum computing era states that all Public Key Cryptography (PKC) standards could become vulnerable in the next few years. The exposure of sensitive data will most likely escalate to other risk scenarios, and this will affect communication networks, electronic transaction verifications, and the security of digital evidence as well.

Quantum-resistant or quantum-safe cryptography standards are currently being implemented and the National Institute of Standards and Technology (NIST) has already chosen the first group of encryption tools that would withstand quantum attacks. This was the result its six-year-long competition. They have also initiated a Post-Quantum Cryptography Standardization project to produce quantum-resistant algorithms.

Quantum Cryptography, more accurately described as Quantum Key Distribution (QKD), is a quantum-safe method introduced to exchange key exchange between two entities. It works by transmitting photons, which are polarized light particles, over a fiber optic cable. QKD protocols are designed according to the principles of quantum physics. Hence, observation or eavesdropping on a quantum state causes perturbation because the unique and fragile properties of photons prevent passive interception. This perturbation will lead to transmission errors. This will be detected by the endpoints, and the key will be discarded. This is used as a verification of the distributed keys. Currently, QKD is just limited to distances of less than 100 kilometers, but satellite proof-of-concept suggests that it can be expanded to more distances over the next few years.

There is an ongoing quantum revolution that will transform entire computer processes, enhancing the security and privacy of communications. However, this may also introduce many new cybersecurity threats. According to the Deloitte poll, organizations are preparing for quantum computing cybersecurity risks. 45% of the respondents are almost complete with their assessments of post-quantum encryption vulnerabilities, and only 11.7% are reported to be taking a wait and see approach for a cyber incident to take place.

There are many Quantum-as-a-Service (QaaS) providers that offer quantum services for researchers, scientists, and developers. Since threat actors might target the QaaS providers and their users, these providers should deploy stringent security protocols in order to access the services. The emerging field of quantum machine-learning could also produce more effective algorithms for identifying and detecting new cyber-attack methods.

The following practices can help your organization prepare for quantum computing cybersecurity:

Many are curious about the revolution of quantum computing and its post-quantum effects. Currently, researchers and scientists are still carefully studying the topic. It is always best to approach the quantum threat as much as any other vulnerability, and prepare for quantum-safe protection.

Dilki Rathnayake is a Cybersecurity student studying for her BSc (Hons) in Cybersecurity and Digital Forensics at Kingston University. She is also skilled in Computer Network Security and Linux System Administration. She has conducted awareness programs and volunteered for communities that advocate best practices for online safety. In the meantime, she enjoys writing blog articles for Bora and exploring more about IT Security.

Editors Note:The opinions expressed in this guest author article are solely those of the contributor, and do not necessarily reflect those of Tripwire, Inc.

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The impact of Quantum Computing on cybersecurity - tripwire.com

April 4, 2023 NVIDIA recently announcedits new system for taking classical computing to the next level utilizing quantum computing. This month, NVIDIA debuted DGX Quantum, the first system to couple GPUs and quantum computing. NVIDIAs new Grace Hopper system has proven to have 10x better performance for applications running terabytes of data. Speed increases like that are extremely valuable to researchers with immense data sets and simulations.

Imagine if a year-long project could be finished in just over a month. Thats the type of increase quantum computing can bring to the table today. As advances in quantum computing continue, and as more supercomputing centers embrace the technology, these times will only get better.

NCSAis one of the supercomputing centers partnering with NVIDIA to utilize these supercharged quantum processing units (QPU). A new special GPU resource will be installed in the National Petascale Computing Facility at the University of Illinois Urbana-Champaign campus. This new resource will be connected to QPU which theIllinois Quantum Information Science and Technology Center(IQUIST) will house in their lab in the Engineering Sciences Building on campus.

Santiago Nuez-Corrales, NCSA research scientist, will be leading NCSAs quantum computing efforts. NCSA has taken its first strides toward a long-term quantum computing strategy, designed to complement ongoing efforts at IQUIST, Nuez-Corrales said when speaking about NVIDIAs announcement. Our target comprises three core activities: understanding and harnessing the potential of existing real and simulated quantum devices as a new form of advanced computing, making quantum technologies accessible to a wide spectrum of users, and identifying application areas where quantum may become a game changer. All three of them draw upon our robust history and expertise with new cyberinfrastructure development, accelerating science-making and meeting the needs of future users. The recent announcement by NVIDIA, hence, arrives serendipitously.

To many unfamiliar with the technology, quantum computing is a tricky topic to define. Contrary to classical computers, you cant even use traditional physics to explain how it works. A quantum computer is a device that harnesses aspects of quantum mechanics, the laws that govern phenomena at the scale of atoms. To put that very simply, what scientists and engineers are attempting to crack is the ability to solve hard problems much faster using quantum mechanics.

Classical computers, the computers most people use every day, represent information by encoding it as 1s and 0s. The collection of all 1s and 0s in memory at any given time corresponds to the state of the computer, which can be changed by programs operating on it. Think of it as a large sequence of on and off switches; despite the sophistication of contemporary microprocessors, classical computers have operated using similar mathematical rules since their inception.

Quantum mechanics turns this on its head by expanding our vocabulary of what the state of a computer and a program can be. Instead of a bit being on or off such as in a classical computer, a qubit, quantum computings version of a bit, can be in both states simultaneously, asuperpositionof these states. Much likeShrdingers cat, the bits are theoretically always an uncertain combination of a 1 and a 0. While creating a fault-tolerant quantum machine is still a ways off, scientists and engineers have devised algorithms that benefit from quantum computing architectures to potentially speed up the solution of problems that are hard to solve with classical ones. With these new quantum resources, certain classes of calculations may happen much faster thanks to a broader palette of operations.

In regards to NVIDIAs recent announcement, Nuez-Corrales explains, DGX Quantum has the potential to decrease the complexity of HPC-QPU integration projects at the hardware level thus lowering the risk of implementation of quantum-classical hybrid cyberinfrastructure. CUDA Quantum extends a mature programming model for GPUs into the QPU world, which will facilitate developing and integrating new quantum kernels across scientific applications. Finally, the ability to access GPU-powered simulators such as those in cuQuantum will help identify new software and scientific pipeline development practices for users to transition from classical to quantum problem-solving.

Greg Bauer, senior technical program manager at NCSA, commented: NCSA is preparing itself to support the adoption of QPUs by research computing projects similar to how NCSA led, in part, the transition to GPUs for research computing with the early evaluation of a PlayStation cluster and deployment of GPU-centric HPC resources.

Increasing adoption of a wide variety of quantum computing technologies at NCSA will have direct benefits to researchers utilizing our resources. At NCSA, Nuez-Corrales says we have identified an initial set of users that may benefit from this collaboration with NVIDIA in terms of access to simulated QPUs and programming models, and later real QPUs. Nuez-Corrales team will use what they learn from this initial project to refine future applications of quantum computing. From this experience, Nuez-Corrales continues, we will gradually become proficient at establishing user support models and resources on campus that remain accessible to our academic community and business partners. More immediately, we are working to integrate these tools into existing GPU-intensive resources such as Delta and provide early access to resources and training for the UIUC research community.

NCSAs Santiago Nuez-Corrales, research scientist, contributed to this story.

Source: Megan Meave Johnson, NCSA

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NCSA Partners with NVIDIA on New Hybrid Quantum Computing ... - HPCwire

Quantum Computing Concept Image.

Quantum machine learning models can achieve quantum advantage by solving a complex class of mathematical problems impossible to crack with a classical computer, according to new research by UBC material scientists.

UBC Blusson Quantum Mater Institute (Blusson QMI) investigator Professor Roman Krems said the results rigorously prove that quantum machine learning does indeed offer the quantum advantage.

The key goal now is to find a real-world machine learning application thatwould benefit from this quantum advantage in practice, said Professor Krems, senior author on the Nature Communications study.

Quantum advantage refers to the instances where quantum computers outperform their classical counterparts when scaling to enormous datasets containing countless variables.

Blusson QMI PhD student and first author of the paper Jonas Jger said the models have universal expressiveness in that they solve not just one problem, but capture the complexity of an entire class of problems that are too complicated to solve with classical machine learning.

While quantum machine learning is often considered to be one of the most promising use cases of quantum computing, there are only a few rigorous results about its real computational advantages, Jger said. Our results offer theoretical guarantees that such advantages indeed exist.

The study proves a quantum advantage exists for two of the most popular quantum machine learning classification models: Variational Quantum Classifiers (also known as quantum neural networks) and Quantum Kernel Support Vector Machines.

We can now confidently explore important real-world applications and develop effective approaches for building informative data encoding quantum circuits that could unlock the full potential of quantum machine learning, said Jger.

The advantages reported in the study are somewhat subject to the quality of the datasets presented to the system. As quantum computing is still in the experimental stage, a challenge faced by researchers is encoding the classical data for processing by a quantum device.

The mathematical problem that weve solved using these models is quite abstract and doesnt have many practical applications. But, because it presents such special properties under the complexity theory, it can be used by others as a benchmark to test how different quantum machine learning models perform, Jger said.

Jger joined UBC in Sept 2022 to commence his PhD studies under the supervision of Professor Roman Krems from UBCs Department of Chemistry and Professor Michael Friedlander from UBCs Computer Science Department.

Professor Krems and his team work at the intersection of quantum physics, machine learning and chemistry on problems of relevance to quantum materials and quantum technologies, including quantum computing, quantum sensing and quantum algorithms.Meanwhile, Professor Friedlander and his research group develop theories and algorithms for mathematical optimization and its applications in machine learning, signal processing and operations research.

Jger hopes to take advantage of their combined expertise to push the limits of quantum computing and develop algorithms that can harness its power for practical applications.

We can now confidently explore important real-world applications and develop effective approaches for building informative data encoding quantum circuits that could unlock the full potential of quantum machine learning.

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New evidence that quantum machine learning outperforms classical ... - UBC Faculty of Science

Quantum Computing Inc. (QCI) reported 2022 total revenue at $135,648 versus no revenue in 2021. Operating expenses were $36.5 million versus $17.1 million in the prior year due to impact of its merger with QPhoton, increase in engineering personnel, non-stock based compensation, and other factors. The net loss was $38.5 million versus $10.7 million in the prior year. The company ended the year with Cash and Cash Equivalents of $5.3 million versus $16.7 million at the end of 2021. After the end of the year, the company has received $6.4 million from sales of $3 million of their shares via an at-the-market facility managed by Ascendiant Capital.

2022 was a pivotal year for the company due to their acquisition of QPhoton which allowed them to offer Quantum Computing as a Service (QCaaS) with a full-stack quantum computing capability. The company has been working on several proof-of-concept projects including projects to optimize sensor placement on a BMW automobile, optimize flight trajectories with VIPC, detect fraudulent banking transactions with Rabobank, optimize windmill placement, optimize nuclear fuel rod replacements, and predict stock performance. They also created a new subsidiary QI Solutions, Inc. to pursue government business.

The company also indicated their roadmap for product development including a Dirac-2 follow-on to the existing Dirac-1 that supports calculations based upon Qudits (0-53 variables) instead of Qubits, a Reservoir Quantum Computer, a Quantum Random Number generator, and other products based upon quantum photonics. The companys goal is to hit EBITDA and cashflow breakeven within 2 years at a revenue level of about $30 million.

For more information about QCIs financial report, you can view their press release posted on their website here.

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Quantum Computing Inc. Announces 2022 Financial Results and Starts Transition to Commercialization - Quantum Computing Report

Lewis Shepherd, senior director of research and emerging technologies strategy at VMware, was added to the technical advisory board of Quantum Computing Inc.

The executive will draw from his more than three decades of government and industry experience in research and development innovation to provide QCI with product visibility, market intelligence and insight, the quantum computing company said Tuesday.

Aside from his responsibilities at VMware, Shepherds career includes time serving at the Defense Intelligence Agency as a senior executive, the Department of Defense as a special government employee and senior adviser, the Federal Communications Commission as a member of its Technological Advisory Council and at Microsoft as general manager and director.

My plan is to add another four to five professionals to the Board whose expertise span a variety of different touch points to quantum, but with the same passion and tireless work-ethic of Lewis, commented Jim Simon, Jr., chair of the technical advisory board at QCI.

Shepards appointment is the third for the QCI board.

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VMware's Lewis Shepherd Joins Technical Advisory Board of ... - ExecutiveBiz

As funding pours into quantum computing, investors are focused on the potential for this technology to address scientific, business and security problems beyond the reach of todays conventional computers. There are signs that dramatic impacts could come in the not-too-distant future, according to industry executives who spoke at the Goldman Sachs 2023 Disruptive Technology Symposium.

A key question during the event was whether the development of quantum computing will follow a path of globalization or fragment into a regional approach. This is particularly relevant at a time when supply chains are on the minds of policy makers and business leaders, having become a source of geopolitical tension and showing indications of fragility during the pandemic.

Ilyas Khan, vice chairman and founder of Quantinuum, said during a panel on quantum computing that he sees the impulse for national control over the development of quantum computing technology. Work his company is doing in the U.S. is subject to a National Security Agreement that is governed by various federal agencies. In many countries, development of quantum computing technology is governed by national organizations, and the intensity of their attention and investment is a historic development, he said.

Im not aware of anything since the Industrial Revolution that even comes close to resembling the resources that are being managed at a national level in order to gain competitive advantage for individual countries, Khan said. When that happens, you get overlap, you get competition, you get suspicion, and in the early days you possibly get fences and borders and walls. And that is what is happening in quantum at the moment. Among many things that may eventually counter these trends and favor globalization, Khan said, will be the willingness of investors and corporate clients to look worldwide for the best ideas in quantum computing.

At the same time, there are significant military and cyber security concerns, as quantum computing is potentially powerful enough to overwhelm existing encryption protocols. The disruption that quantum computing promises wont just be in the business sphere but also in the national security arena, Stephen Nundy, chief technology officer for Lakestar, a European venture capital fund, told the symposium.

Nundy suggested this lends added urgency to questions about who will lead in developing this new technology. Europeans mostly watched from the sidelines as U.S. companies scaled up cloud computing businesses that are now dominant, he said, and they should be wary of doing the same in quantum computing. Europe would be making a poor choice to simply wait for a copy of the blueprint of quantum technology from the U.S. or Asia, rather than developing its domestic industry and expertise, he said.

Interdependence is another theme that is emerging as the quantum computing technology ecosystem develops. Pia Lemmetty, head of finance for IQM Quantum Computers in Finland, described her companys decision to build a pilot foundry for quantum processors. The initial aim was to be able to design chips and manufacture them in-house, but other startups that dont have foundry capability have started reaching out, she said. It will be very important to think about the European angle and ensure that we have capabilities in Europe to be self reliant on the hardware development side, Lemmetty said.

Lemmetty said her company is already beginning to work with corporate clients to design adaptations of quantum computing algorithms and solutions and then to develop hardware specifications to address industry-relevant problems. This will help ensure that businesses are building expertise and are enabled when a quantum advantage emerges, she said. The time is very much now to start doing that.

Markus Pflitsch, founder and CEO of Terra Quantum, agreed that corporate clients should start building relationships and expertise now. His Switzerland-based company is developing quantum algorithms, software that can run today on classical computers, while the development of quantum hardware proceeds. This hybrid approach, using simulated qubits, is already demonstrating some of what may be possible collective portfolio modeling for the investment industry, for example, or optimized satellite mission planning.

These algorithms may begin to reach their full potential when the hardware advances. But Pflitsch said companies should recognize the coming disruption and begin to work with quantum computing technology as soon as possible. We have a growing number of clients, Pflitsch said. We can deliver business value today.

This article is being provided for educational purposes only. The information contained in this article does not constitute a recommendation from any Goldman Sachs entity to the recipient, and Goldman Sachs is not providing any financial, economic, legal, investment, accounting, or tax advice through this article or to its recipient. Neither Goldman Sachs nor any of its affiliates makes any representation or warranty, express or implied, as to the accuracy or completeness of the statements or any information contained in this article and any liability therefore (including in respect of direct, indirect, or consequential loss or damage) is expressly disclaimed.

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Can Europe Beat China and the US in Quantum Computing? - Goldman Sachs

After some of the basics of quantum computing are explored in the introductory episode of the Entrust Engage podcast, episode two takes listeners deeper into the science behind this topic with an interview featuring Dr. Carmen Palacios-Berraquero, award-winning quantum physicist and CEO of Nu Quantum. Many interesting areas were covered from a brief history of quantum computing to what the future benefits of this field might be. Here are the 6 key takeaways from this episode:

#1: The episode kicked off with a concise history of quantum computing, which goes back to the 80s when people first began to look at how to apply quantum theory to computing. Then in the 90s, Shors algorithm was developed, which significantly sped up the calculation of factorization problems and was the first step in potentially breaking RSA encryption. Experimental physicists also found new hardware in which you could encode quantum information. Progress in quantum computing continued to exponentially accelerate in the 2000s and 2010s and led to a kind of modern-day space race of different hardware approaches. In these earlier years the field was still largely an academic endeavor, whereas in the past seven years the academic pioneers of this race moved into the industry to set up startups. In 2019, Google declared quantum supremacy. And in 2021, more than $3 billion was invested into quantum computing, further cementing its importance to the future of technology.

#2: So, what exactly is quantum supremacy? For starters, Dr. Palacios-Berraquero prefers the term quantum advantage. When Google announced that it had achieved this, what did that really mean? How significant was this?

Well, Google was essentially successful in using quantum computing to solve a problem that would have been infeasible for a classical computer. However, the problem it solved had no application in the real world. While the industry is moving toward solving commercially useful problems, there is still progress to be made before any organization can consider itself to have a true quantum advantage.

#3: There is consensus that the quantum computing threat to traditional public key algorithms will be a reality within the decade. However, taking Googles 2019 claim of quantum supremacy into consideration, the question arises: Has this timeline been accelerated?

The answer: not necessarily. There are two main factors to consider here. The first is that it is very hard to scale these machines. The second is that there are lots of errors in quantum computers processors. Error correction schemes are very complex and take up quite a few logical qubits in quantum computers, leaving fewer qubits to perform logical computations. So, even with the progress made at present, the threat timeline of quantum computers has not accelerated.

#4: Is the news about quantum computing all about its threats and challenges? Echoing what we learned from episode one, absolutely not! There are major benefits that quantum computing can unlock in the future. For starters, quantum computing can crack those intractable problems we cant currently solve today. This opens entirely new applications, markets, and industries. Some examples include both material and drug design, paving the way for innovations in healthcare and the battle against climate change. In the near term, quantum computing promises benefits like financial portfolio optimization, improvements in machine learning algorithms, and the simulation of quantum and physical systems.

#5: What is a quantum random number generator and how different is it from what we know of entropy in cryptography today? The quantum random number generator is based on the main proposition of quantum theory that the outcome of a measurement is completely unpredictable. It uses this principle to generate entropy/random numbers. Over the past decade, it has been proposed to use these generators as a source for cryptography.

The main difference is that entropy used in cryptography currently is based on classical mechanics, where theoretically everything is predictable. In theory, by knowing the exact functioning of a system and combining it with a lot of computing power, you could predict the outcome of a classical random number generator.

The reality is quite different, though. Current cryptography uses mathematical tools in addition to a random number generator, making it quite impossible to crack. While the industry is debating the use and applications of a quantum random number generator, its still a long way from adopting it in cryptography.

#6: Additional benefits in development include quantum computing as a service (QCaas) and quantum internet. These are two very different things. QCaaS is a means by which users can access quantum computers via the cloud. For example, AWS hosts around five quantum computers, and a user can buy time on them through the cloud and run various algorithms. And theres a long line of users queued up to use these computers. Who are these users? A mix of academics and researchers as well as R&D departments in industry. However, these machines are still in the labs of companies, and it will be a while before they can function independently in a data center.

Now lets unravel the service known as quantum internet. Picture a computer network that can send quantum information between distant computers, and there you have it in a nutshell. This technology is still largely contained to the realm of academia, and its still unknown what the exact commercial application will be. What we do know is that its still some years away.

The science behind quantum computers is pretty fascinating, and if youre looking to learn more, I recommend listening to the second episode of Entrust Engage. For more information and resources on post-quantum and how to prepare, visit our webpage.

The post 6 Things I Learned About the Science of Quantum Computing from Entrust Engage appeared first on Entrust Blog.

*** This is a Security Bloggers Network syndicated blog from Entrust Blog authored by Lavanya Suvarna. Read the original post at: https://www.entrust.com/blog/2023/04/6-things-i-learned-about-the-science-of-quantum-computing-from-entrust-engage/

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6 Things I Learned About the Science of Quantum Computing from Entrust Engage - Security Boulevard