Category Archives: Quantum Computer
Breaking Down Quantum Computing: Implications for Data Science and AI – KDnuggets
Quantum computing has had a transformative impact on data science and AI, and in this article, we will go far beyond the basics.
We will explore the cutting-edge advancements in quantum algorithms and their potential to solve complex problems, currently unimaginable with current technologies. In addition, we will also look at the challenges that lie ahead for quantum computing and how they can be overcome.
This is a fascinating glimpse into a future where the boundaries of technology are pushed to new frontiers, greatly accelerating AI and data science capabilities.
Quantum computing involves specialized computers that solve mathematical problems and run quantum models that are quantum theory principles. This powerful technology allows data scientists to build models related to complex processes such as molecular formations, photosynthesis, and superconductivity.
Information is processed differently from regular computers, transferring data using qubits (quantum bits) rather than in binary form. Qubits are vital in terms of delivering exponential computational power in quantum computing as they can remain in superposition - we will explain this more in the next section.
Using a wide range of algorithms, quantum computers can measure and observe vast amounts of data. The necessary algorithms will be input by the user and the quantum computer will then create a multidimensional environment that makes sense of the various data points to discover patterns and connections.
To gain a better comprehension of computing, it is important to gain an understanding of four key terms; qubits, superposition, entanglement, and quantum interference.
Qubits
Qubits, short for quantum bits, are the standard units of information used in quantum computing, similar to how traditional computing uses binary bits. Qubits use a principle known as superposition so that they can be in multiple states at one time. Binary bits can only be 0 or 1, whereas Qubits can be 0 or 1, just a part of 0 or 1, or both 0 and 1.
While binary bits are typically silicon-based microchips, qubits can consist of photons, trapped ions, and atoms or quasiparticles, both real and artificial. Because of this, most quantum computers require extremely sophisticated cooling equipment to work at very cold temperatures.
Superposition
Superposition refers to quantum particles that are a combination of all possible states, and these particles can change and move while the quantum computer observes and measures them individually. A good analogy to explain superposition is the various moments a coin is in the air when it is tossed.
This allows the quantum computer to assess each particle in many ways to find different outcomes. Instead of traditional, sequential processing, quantum computing can run a huge number of parallel computations at once thanks to superposition.
Entanglement
Quantum particles can correlate with each other in terms of their measurements, creating a network known as entanglement. During this engagement, the measurement of one qubit can be used in calculations that are made by other qubits. As a result, quantum computing can solve extremely complex problems and process vast amounts of data.
Quantum Interference
During superposition, qubits can sometimes experience quantum interference, the likelihood of qubits becoming unusable. Quantum computers have measures in place to try to reduce this interference to ensure the results are as accurate as possible. The more quantum interference, the less accurate any outcomes are.
Quantum machine learning (QML) and quantum artificial intelligence (QAI) are two underappreciated, but fast-growing fields within data science. This is because machine learning algorithms are becoming far too complex for traditional computers and require the capabilities of quantum computing to process them effectively. Eventually, this is expected to lead to major advancements in artificial intelligence.
Quantum computers can effectively be trained in the same way as neural networks, adapting physical control parameters to solve problems, such as the strength of an electromagnetic field or the frequency of laser pulses.
An easy-to-understand use case is an ML model that could be trained to classify content within documents, doing so by encoding the document into the physical state of the device so it can be measured. With quantum computing and AI, data science workflows will be measured in milliseconds, as quantum AI models will be able to process petabytes of data and compare documents semantically, providing the user with actionable insights beyond their wildest imagination.
Major players such as Google, IBM, and Intel have invested heavily in quantum computing but as yet the technology is still not deemed a viable and practical solution at a business level. However, research in the field is accelerating and the technical challenges involved with quantum computing will surely be ironed out with machine learning sooner rather than later.
IBM and The Massachusetts Institute of Technology (MIT) can be credited with unearthing the experimental research that showed it was possible to combine machine learning and quantum computing back in 2019. In a study, a two-qubit quantum computer was used to demonstrate that quantum computing could boost classification supervised learning using a lab-generated dataset. This has paved the way for further research to outline the full potential of this technological partnership.
In this section, we will provide details of the quantum computing projects launched by Google and IBM, giving an insight into the enormous potential of the technology.
Thanks to this ongoing research and education, quantum computing could power machine learning models that can be applied to various real-world scenarios. For example, in finance, activities such as investing in stocks and using AI signals for options trading will be supercharged by the predictive power of quantum AI. Likewise, the advent of physical quantum computers will spur a revolution in terms of using kernel methods for linear classification of complex data.
There are still significant steps that need to be taken before quantum machine learning can be introduced into the mainstream. Thankfully, tech giants such as Google and IBM are providing open-source software and data science educational resources to allow access to their quantum computing architecture, paving the way for new experts in the field.
By accelerating the adoption of quantum computing, AI and ML are expected to take giant leaps forward, solving problems that traditional computing cannot facilitate. Possibly even global issues such as climate change.
Although this research is still in its very early stages, the potential of the technology is quickly becoming apparent and a new chapter of artificial intelligence is within reach.
Nahla Davies is a software developer and tech writer. Before devoting her work full time to technical writing, she managedamong other intriguing thingsto serve as a lead programmer at an Inc. 5,000 experiential branding organization whose clients include Samsung, Time Warner, Netflix, and Sony.
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Breaking Down Quantum Computing: Implications for Data Science and AI - KDnuggets
The Quantum Computing Cryptopocalypse Ill Know It When I See It – Security Affairs
The Quantum Computing Cryptopocalypse Ill Know It When I See It
Can quantum computing break cryptography? Sure, it can. Can it do it within a persons lifetime? Yes. In fact, it will likely achieve this sometime within your career. Will it be a cryptopocalypse, as some experts suggest? Possibly. Advances in quantum computing mean that we dont necessarily have to wait for a large quantum computer running at supercooled strengths at sufficient qubits to run Shors algorithm (the best-known algorithm for factoring large numbers). There are newer, more sophisticated techniques on the table, such as combinations of attacks that can do what one brute force thing cant. So, it might not be time to panic, but it certainly is time to recognize that the threats and the benefits of quantum computing are here now, and security professionals need to ensure that they and the organization they work for are fully prepared.
These are just some of the thoughts that Johna Till Johnson, CEO at Nemertes Research, and Bob Burns, Chief Product Security Officer at Thales, shared with me on the latest episode of the Security Sessions podcast. Quantum has been discussed and theorized for years, and like the sudden rise of AI and generative technology that seemed to happen in early 2023, efficient and cost-effective use of quantum computing may also jump to a critical mass, and sooner than expected, despite its long voyage of research and development.
Bob asks, for example, What happens if we find that quantum computing actually can be used as a multistage step to break the factoring that doesnt involve Shors algorithm? What if we make incremental improvements or chain multiple results from a quantum computer thats realizable today? Those are the types of thoughts that keep him up at night. They are a testament to peoples relentless desire for innovation, as well as their abilities to advance by developing techniques, products, and solutions that werent even foreseen when the technology was first introduced.
You can say such things about almost any technology, of course the personal computer, the internet, and the smartphone they all became much more versatile than their inventors ever foresaw. But Johna provides an example of how this evolution in breaking cryptography happened just recently: researchers from the KTH Royal Institute of Technology in Stockholm used recursive training AI combined with side-channel attacks to crack one of NISTs quantum-resistant algorithms. In this case, it measured out-of-band information, specifically temperature changes corresponding to the processing inside the machine.
This has direct and ominous implications on what is known as a Q-Day that point in time when quantum computers can render all current encryption methods meaningless, as PCMagazine succinctly puts it. But as Bob points out, for calculating a Q-Day, I look at all my data, and I take the biggest amount of data that I want to keep the longest amount of time, and I predict how long it might take me to make that transition. But when my Q-Day ends up being, lets say, ten years away, my concern will be that someone forces that up to three of four years.
But both Johna and Bob point out that quantum computing is not all doom and gloom. There are lots of good reasons to deploy quantum computing, and many arent what most people think they are. Basically, Johna says they can solve problems for which the answer isnt the best or the only, but good enough by some consistent definition of good enough, for example, policy hardening. Whether this refers to a technical policy, a cybersecurity policy, or even a geopolitical policy, its helpful to know all the answers. In the latter case, a government might need to identify all the possible things it can do that will not result in war with a particular country. Thats the kind of thing that a classical computer with AI cant answer very well, but a quantum computer can because it effectively computes all the possible scenarios and outcomes at once. Its not great at telling you which of those scenarios is the absolute best, but it can help decision-makers draw a line to say, anything above this line, we dont go to war, and thats good enough.
Essentially, this is about taking on the category of problems that we dont even try to solve right now because theyre too hard; they require a technique of solving all possible scenarios at once and cherry-picking the ones that come above some definition of good enough. And those are all the problems that quantum can solve. Johna concludes, Once you let your imagination go with that, policy hardening is just kind of the tip of the iceberg.
About the author: Steve Prentice
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PierluigiPaganini
(SecurityAffairshacking, quantum computing)
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The Quantum Computing Cryptopocalypse Ill Know It When I See It - Security Affairs
Taiwan Targets Domestic Quantum Computer Production by 2027 – Quantum Computing Report
Taiwans National Science and Technology Council (NSTC) has announced its objective to domestically manufacture a quantum computer by 2027, marking a pivotal advancement in computational power, according to NSTCs Department of Natural Sciences and Sustainable Development Head, Luo Meng-fan. Collaborating with the Ministry of Economic Affairs and Academia Sinica, the NSTC is implementing a five-year, NT$8 billion (US$258.86 million) quantum technology initiative initiated in 2022.
Highlighting the potential of quantum computing, Luo referenced a Google study revealing remarkable speed in completing a random circuit sampling task on its Sycamore processor with 70 quantum bits (qubits), showcasing superior computational efficiency compared to classical supercomputers. Acknowledging security concerns regarding the eventual ability of quantum computers to breach digital code protections, Luo emphasized the importance of countermeasures like quantum cryptography.
While recognizing the current challenges, including high error rates, Luo projected that six more years of research and development are essential for quantum computing to reach maturity and make a global impact. Emphasizing the strategic significance for Taiwan to pioneer quantum technologies, NSTCs collaboration with academia and industry aims to streamline the quantum computer component supply chain. Additionally, Taiwan is engaging with Finnish quantum computing hardware company IQM for potential testing platforms and leveraging quantum cloud computation services from global players like IBM and Amazon. For further details, you can read an article posted in the Taipei Times which can be accessed here.
January 10, 2024
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Taiwan Targets Domestic Quantum Computer Production by 2027 - Quantum Computing Report
Quantinuum partners with Riken for hybrid quantum supercomputing platform – DatacenterDynamics
Quantum computing company Quantinuum has agreed a deal with Japanese research institution Riken to supply a H1-Series quantum computer.
Powered by Honeywell, the Quantinuum H1-1 ion trap quantum computer which contains 20 fully connected qubits that sit across five Quantum Charged Coupled Device (QCCD) zones.
Under the terms of the agreement, Quantinuum will install the hardware at Rikens campus in Wako, Saitama, with the deployment forming part of the research labs project to build a quantum-HPC hybrid platform consisting of high-performance computing systems. This will be Quantinuum's first on-premise delivery of a system.
Supported by the New Energy and Industrial Technology Development Organization (NEDO), a national research and development agency under Japans Ministry of Economy, Trade and Industry, the project aims to demonstrate the advantages of hybrid computational platforms.
Researchers from Riken also plan to collaborate with Softbank, University of Tokyo, and Osaka University to develop the software tools and applications necessary for the effective integration of quantum and supercomputers.
Riken is home to Japans first quantum computer, which went online in April 2023. That superconducting machine currently has 64 qubits, but the institute has acknowledged the computer will need to increase this number to one million qubits to become more widely used.
Advanced quantum computers of NISQ are now moving into the practical stage as the number of qubits is increasing and the fidelity is improved, said Dr. Mitsuhisa Sato, deputy director at Riken, and director of the labs quantum HPC collaborative platform division.
Riken is committed to developing system software for quantum-HPC hybrid computing, by leveraging its comprehensive scientific research capabilities and experience in the development and operation of cutting-edge supercomputers such as Fugaku, he said.
Quantinuum was founded in 2021 when Honeywell spun out its Quantum Solutions division and merged it with UK quantum computing startup Cambridge Quantum Computing.
In May 2023, the company announced the launch of its System Model H2 which contains 32 qubits capable of all-to-all connectivity. According to Business Insider, the H2 occupies around 200 sq ft in a data center in Denver, Colorado. It is reportedly one of two prototype machines in the facility.
Honeywell owns a 54 percent stake in Quantinuum. IBM is also an investor.
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Quantinuum partners with Riken for hybrid quantum supercomputing platform - DatacenterDynamics
2023: A Year of Growth and Collaboration for Quantum Computing – The Quantum Insider
By John Levy
CEO, Co-Founder and Chair, SEEQC
In 2023, the quantum ecosystem experienced significant strides in research and development, with companies big and small contributing to the industrys overarching goals.
The culmination of these advances proves that collaboration and competition is the best approach to bring quantum computing to life. For a technology with as much potential to alter computing as we know it, we must collaborate within, and outside of, our industry to ensure its success.
The achievements in 2023 are strong evidence of the positive trajectory of the industry, with numerous innovations from many different quantum computing companies, global expansion of the technology, and cross-sector collaborations vital to the development and implementation of quantum computing.
Breakthroughs
Error correction, a key focus for quantum computing, is essential for scalability; the most successful quantum computers will be defined by this metric, among many others. In February, Google published promising results, finding that a 17-qubit system could successfully recover from one error, and a 49-qubit system could recover from two simultaneous errors. This was a major milestone in Googles quantum roadmap as it continues to be a key contributor to the quantum landscape. And in November, Amazon introduced a new chip for quantum computing which has suppressed errors by 100x. According to Amazon, combining passive and active error correction approaches could theoretically achieve quantum error correction six times more efficiently than standard methods. IBM Scientists discovered a new error correction scheme that work with 10x fewer qubits, a discovery that has enabled IBM to clarifying its roadmap for the next decade.
This year, our long established partner, Riverlane, introduced an error correction decoder chip that shows promise for tackling the complexity of decoding large arrays of error corrected qubits. This work however also highlights the latency and bandwidth bottlenecks associated with decoding error correction architectures at scale. Multi-stage decoder strategies like those by Microsoft, Riverlane and our scientific consultant, Simon Trebst, prove that pre-decoding is key to eliminating these latency and bandwidth bottlenecks while also proving that a chip-based solution integrated with qubits at the chip level is critical to unlocking these benefits. In 2024 we look forward to defining the worlds first integrated chip-based decoder architecture to prove our chips are the solution to scaling all quantum computers.
Quantum computers must also be scalable and energy efficient to make a meaningful impact. In March, SEEQC debuted its first quantum reference system, SEEQC System Red. This milestone was celebrated in July with a collaboration with HQS Quantum Simulations, in which SEEQC Red successfully ran HQSs algorithm for the first time on real hardware. Collaborations like this and others define (and prove) the commercial applications that this technology can provide.
Later in the year, SEEQC introduced its first fully digital chipset for full-stack quantum computers, capable of control and multiplexing. SEEQC takes a different approach to scalability, using SFQ chip methodology as opposed to cryo-CMOS, the latter of which has been used to scale modern computing chips. SEEQCs digital single flux quantum (SFQ) chips will be capable of running all core qubit controller functions of a quantum computer at the same cryogenic temperature as the qubits, a significant development for energy efficiency in quantum.
As quantum chips continue to grow in power and capability, legacy chip providers are also significantly expanding the quantum ecosystem such as the debut of Intels spin silicon 12-qubit chip in June. The experience, expertise and resources of these legacy companies allow for smaller companies to dynamically improve upon their findings and advance their technology alongside these industry leaders.
It is impossible to discuss scalability and energy efficiency without addressing the need for larger qubit arrays which hold the potential for larger systems. Atom Computing was the first company to reach 1,000 qubits in a quantum computer, followed up by IBMs 1,000 qubit system, unveiled in December. These are grand milestones in showcasing the power that these quantum computers can hold, but there is still much to do surrounding error correction, scalability and coherence to make these systems commercially applicable.
Quantum continues to go global
Quantum expanded globally this year, with some pivotal firsts in validating the technology occurring across the globe.
IQM was selected to deliver the first processing units for quantum computers to Spain. Like many governments globally, Spain is committed to being a part of the quantum landscape, and its presence strengthens Europes regional quantum industry.
Similarly, Japans first gate-based quantum computer from the Riken Research Institute went live, solidifying the APAC regions role in the development of applicable and useful quantum computing. Japans first gate-based quantum computer is a significant milestone for the country, the region and the industry as a whole.
One month later, SEEQC built Italys first full-stack quantum computer at its facility in Naples. The Italian government has signaled that quantum computing is an immediate priority, and will invest significant resources over the next few years in hopes of establishing itself as a leader in this field.
For quantum computing to make the global impact that it has the ability to do, nations must collaborate for the growth and betterment of the technology. These achievements from 2023 paint a picture of a flourishing global industry, and 2024 will bring more important developments for international quantum computing.
Collaboration opens the door for quantums future
One of the most impactful ways for quantum development is cross-industry partnerships and collaborations, combining the resources and expertise from leaders in their respective fields with a conjoined goal. These collaborations are taking place across the world making it impossible to list all of them, which speaks volumes to the global demand for quantum computing in a number of industries.
The leading industry ripe for application is the medical and pharmaceutical field. IBM and Moderna announced a collaboration to research how quantum computing and generative AI can positively impact mRNA science; IBM will give Moderna access to quantum computing systems to research the capabilities of quantum computing in pharmaceuticals.
Leveraging expertise from todays classical computing leaders is a significant resource for quantum computing. NVIDIA has invested considerably in their position in quantum computings landscape, announcing a number of quantum-focused collaborations. One of these projects with SEEQC pursues the worlds first CPU, GPU and QPU chip integration to create a singular high-powered system with infrastructure for quantum AI and other applications.
Its imperative that quantum computing embraces the role of academia in its growth as an industry. Harvard, in collaboration with QuEra, created the first programmable, logical quantum processor, capable of encoding up to 48 logical qubits. This processor has also executed hundreds of logical gate operations, showing significant progress for the performance of neutral atom quantum computing systems.
It has been a year of promising advancements and critical milestones in quantum computing. It will take an ecosystem of thoughtful and innovative companies, not one winner, to propel quantum computing into the realm of useful technologies, and that is reflected in 2023s accomplishments.
While its important to reflect, its much more impactful to look ahead: 2024 holds great promise for our industry. Collaborations will continue to thrive and teach us all about the capabilities of quantum technology. Technology will continue to progress and make significant strides that were once unimaginable. And as CHIPS and Science Act funds begin to directly impact the quantum computing industry, the best is yet to come for my colleagues in the quantum computing industry.
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2023: A Year of Growth and Collaboration for Quantum Computing - The Quantum Insider
Artificial Intelligence & Quantum Computing the Next Big Thing? – Medium
How can Quantum Physics empower AI?Photo by Anton Maksimov 5642.su on Unsplash
Quantum computers based on quantum physics can be much faster than normal computers, at least in solving some mathematical problems. How can the area of artificial intelligence, data science & Co. profit?
First lets look into what a quantum computer is and why they are faster:
A quantum computer uses qubits, which can exist in superposition and be entangled, to perform computations. By leveraging these quantum properties and applying quantum gates, quantum algorithms can solve certain problems more efficiently than classical computers. However, building practical and scalable quantum computers is still an active area of research, and many technical challenges need to be overcome before they can be widely deployed[1][2}.
So now to the question of how quantum computing could possibly enable faster processing times for AI models. In the future, quantum computers could solve certain problems much more efficiently than ordinary computers by exploiting the unique properties of the subatomic world.
Experts have been wondering whether these problems could also include machine learning. This is a form of artificial intelligence in which computers look for patterns in data and learn rules that they use to draw conclusions even in unknown situations[3]. So yes quantum computing can be much faster but is the answer exact enough?, since we have learned that this output is probabilistic so the output can be different although the input is the same. So the unanswered question is whether there are scenarios in which quantum machine learning offers an advantage over the classical variant?
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Artificial Intelligence & Quantum Computing the Next Big Thing? - Medium
3 Quantum Computing Stocks to Make You the Millionaire Next Door: 2024 Edition – InvestorPlace
Millionaire-maker quantum computing stocks are inherently risky but offer massive payoff
Source: Boykov / Shutterstock.com
Quantum computing is the next evolution of computing. Its benefit is that, at its core, it is capable of solving problems that classical computers cannot. Classical computers often rely on brute force to find solutions to complex problems. However, like all things, there is a barrier. These millionaire-maker quantum computing stocks will push computing past its current limits.
Faster computing times have vast applications. Just about everything today relies on computers and, as the field develops, investment is sure to rise. That makes the quantum computing stocks below incredibly interesting. Compound annual growth rates in the sector are expected to reach above 38% between 2023 and 2028. Thus, an investment today could yield substantial returns for millionaire-maker quantum computing stocks.
Source: Amin Van / Shutterstock.com
IonQ (NYSE:IONQ) has developed the IonQ Forte quantum computer, while emerging as one of the sectors top stocks.
Its shares have really blossomed in 2023, providing investors with strong returns but not returns without volatility. The companys shares were below $4 at the beginning of the year, but shot up to almost $20 in August. It currently resides at around $12. So, it was both rewarded and punished in 2023.
The companys Forte quantum computers are currently available through the three leading Cloud providers; Amazons (NASDAQ:AMZN) AWS, Microsofts (NASDAQ:MSFT) Azure and Alphabets (NASDAQ:GOOG, NASDAQ:GOOGL) Google Cloud.
Company revenues grew by 122% in the third quarter, reaching $6.1 million. While that was above the high end of guidance, Its 22 cent EPS was 7 cents lower than expected. Yet, the company increased its guidance for the full year to a high of $22 million from a previous high of $19.3 million.
Source: Shutterstock
FormFactor (NASDAQ:FORM) is an interesting, diversified way to play the emergence of quantum computing stocks. The company is not primarily engaged in the business of quantum computing. Instead, FormFactor is a semiconductor company.
The company sells probe cards which are used for chip testing. Semiconductor testing and measurement is a growing, high-margin business worthy of investment.
However, FormFactor also recently released a quantum computing chip which has thrust it into the conversation relating to quantum computing. Clearly, FormFactor is a more diverse and potentially lower-risk option in millionaire-maker quantum computing stocks.
Financially, the stock is somewhat of a mixed bag: Earnings were roughly 17% better than expected but revenues were roughly 4% lower than anticipated. The company shares are also relatively well established and trade for just over $37. Thus, they dont have the same runaway growth potential as IonQs, for example. Nevertheless, they do have the potential to provide substantial returns in the future.
Source: Shutterstock
Quantum Computing (NASDAQ:QUBT) is, in my opinion, the stock with the most potential to create millionaires. The company is very small and produced a mere $50,000 in revenues in the third quarter.
That revenue is largely attributable to the provision of professional services to both public and commercial firms. Although the companys revenues continue to be small, there is a positive to take from its most recent earnings report: Revenues increased by 111% during the first nine months of 2023, reaching $283,000.
Quantum Computing has released five products over the previous 17 months, completed its first hardware sale and begun to build out of its quantum chip facility. Although its revenues remain modest, the company is resolute that at some point its continued ability to progress will lead to large contracts.
The company has developed a particularly strong relationship with NASA, securing its third subcontract award from the agency in July. Its clear that the government will continue to fund the development of the field. If Quantum Computing can provide results, the skys the limit.
On the date of publication, Alex Sirois did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.
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3 Quantum Computing Stocks to Make You the Millionaire Next Door: 2024 Edition - InvestorPlace
The Future of Quantum Computing in Environmental and Health Sciences – The Quantum Insider
Insider Brief
PRESS RELEASEUniversity of Waterloo/December 15, 2023Practical and scalable quantum computers are still in the early stages of development, and many technical challenges need to be overcome before they can be widely used for various applications. Researchers and companies globally, as well as right here at the University of Waterloo, are diligently pushing the boundaries of quantum computing technology, driving forward innovations in this emerging field.
The Transformative Quantum Technologies (TQT) program hosted its annual Quantum Opportunities and Showcase on December 14, at the Research Advancement Centre 2 (RAC2).
TQT is a collaborative research initiative supported by the Institute for Quantum Computing (IQC) at Waterloo. It aims to accelerate the development and use of impactful quantum devices. The University is not only dedicated to ground-breaking research but has spun out more than 15 quantum startups. This combination of world leading facilities, researchers and innovations is why Waterloo is referred to as Canadas quantum valley.
The showcase delivered a deep dive into the world of quantum technologies and their potential applications in the fields of environmental and health sciences. The event allowed for researchers, students and industry to come together and discuss ways to advance the field and provide examples of the capabilities of quantum computing. The day included insightful panels, presentations and a tour of the state-of-the-art research labs at the IQC and TQT.
Left to right: Tracey Forrest, program director, TQT, Shirley Tang, associate dean, research, Faculty of Science, Alexandre Cooper-Roy, research associate and senior technical lead, Quantum Simulation and Transformative Quantum Technologies, Weinan Zhao, postdoctoral fellow, Neil Rowlands, engineering fellow, Honeywell Aerospace
Kicking things off in a panel discussion on quantum in the environment, experts discussed where quantum could help in the future when it comes to measuring, monitoring and mitigating the environmental impacts of human activity on the atmosphere, our oceans and in our terrestrial ecosystems.
All this environmental monitoring, data collection and processing takes immense computing power. Quantum computers have the potential to solve certain problems much faster than traditional computers. They are particularly well-suited for tasks such as factoring large numbers, searching large databases and simulating systems, which are challenging for traditional computers to handle efficiently.
In addressing the vast challenges of monitoring water, air and soil impacted, the current system of sequential sampling is economically impractical due to the extensiveness and remoteness of areas involved, said Dr. Shirley Tang, associate dean of research in the Faculty of Science. To overcome this, quantum technology may offer a promising solution by enabling simultaneous monitoring of multiple sites using remote sensor technology, revolutionizing our approach to understanding environmental changes.
The panel also discussed how using quantum computing for environmental assessment raises challenges as quantum sensors may work well in a lab environment, but do not fare well in rugged terrain.
I encourage reaching out to potential beneficiaries of quantum technology, understanding their specific needs and adoption criteria, Alexandre Cooper-Roy said, a research associate and senior technical lead for Quantum Simulation and Transformative Quantum Technologies. Mining companies, operating in noisy and dirty environments, they have a very different operation criteria than what happens in the lab. So, its very important to engage at the earlier stage.
Left to right: Dmitry Pushin, professor, Department of Physics and Astronomy, Michael Reimer, professor, Department of Electrical and Computer Engineering, Troy Borneman, senior scientist, High Q Technologies, Michal Bajcsy, professor, Department of Electrical and Computer Engineering, Subha Kalyaanamoorthy, professor, Department of Chemistry
The health panel explored ways that quantum technologies could be used in a range of applications from medical imaging to drug discovery and the development of personalized medicine.
A recurring theme was how quantum scientists need to regularly consult with end users of quantum devices from technicians to clinicians.
Our quantum device, designed for high sensitivity, became more impactful when we identified real-world problems through conversations with those who could guide us in integrating it into their workflows, Troy Borneman said, a senior scientist at a quantum startup called High Q Technologies. This approach proved effective in making a meaningful impact, especially in addressing economic and time efficiency concerns in large biological or health problems.
In our case at High Q Technologies, we recognized a significant challenge in biology related to understanding protein folding and structural biology. This led us to design a system with high sensitivity for electron paramagnetic resonance, a crucial aspect for pharmaceutical companies and their drug development techniques, Borneman said.
After the panel discussions, the potential of quantum applications came to life through insightful posters and guided tours of the quantum labs at the Research and Advancement Centre (RAC2). Waterloos students and researchers presented how they use the cutting-edge equipment to develop their innovative projects and discussed possible commercialization avenues, establishing foundations for tangible impact.
Right: Graduate student Connor Kapahi demonstrates quantum opportunities in optometry
This showcase highlights Waterloos leadership in advancing quantum computing, a developing scientific field, to generate new technologies for positive human progress in the realms of environmental and health sciences.
The TQT program has demonstrated agility in addressing needs and providing ongoing support for ambitious research-to-application activities, as discussed today, said Tracey Forrest, program director, Transformative Quantum Technologies. Since its launch in 2016, TQT has assisted more than 600 researchers, including students, postdocs and nearly 50 faculty members at the University of Waterloo.
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The Future of Quantum Computing in Environmental and Health Sciences - The Quantum Insider
How Quantum Computing Trends Will Impact Pharma in 2024: Q&A With Erik Huestis, Partner at Foley Hoag – Pharmaceutical Executive
Huestis discusses the ways that quantum simulation and quantum systems can be used in areas such as drug discovery and the creation and protection of intellectual property in the life sciences industry.
Erik Huestis, a partner at the law firm Foley Hoag, serves as co-chair of the firms technology industry group. He recently discussed how quantum computing may be used in the coming year by the life sciences and biotech industries.
Pharmaceutical Executive: What are the benefits of using quantum computing over classical computing for the pharma industry?
Erik Huestis: The exciting thing about quantum computing, as compared to classical computing, is that it is inherently easier to simulate quantum systems using quantum systems. Particularly in the near term, quantum simulation is whats most exciting to me. The application in biotech is that its extremely computationally prohibitive to compute attributes of molecules, of complex compounds in a classical regime, but quantum simulation and universal quantum computing allows us to compute those properties of pharmaceutically interesting molecules on a reasonable time scale with reasonable precision. That feeds directly into the discovery pipeline.
PE: How can innovators in biotech create and protect quantum intellectual property?
Huestis: In biotech in particular, the focus is going to be on the algorithm side, as opposed to the hardware side. The average biotech isnt developing new lasers or chips, but they are in a unique situation to create new algorithms, both purely-quantum and quantum-classical hybrid.
On the purely quantum side, optimized algorithms for predicting the kinds of properties that a pharmaceutical company cares about is an interesting avenue. More broadly, there are some really interesting avenues combining quantum computing into hybrid solutions. For example, bringing to bear these quantum algorithms that have an advantage of classical algorithms as part of an end-to-end artificial intelligence driven development pipeline.
It's very tempting to conflate quantum computing and AI, but theyre very different. There is a whole suite of problems, however, that quantum computing is really good at solving that work nicely into broader AI systems. When I think of a biotech and protection opportunities, my mind goes to what kind of system architectures combining quantum computing and drug discovery and screening processes are being solved.
PE: Will 2024 be the year that quantum computers break-through, similar to how AI performed in 2023?
Huestis: Its important to be a little more fine grained about that analysis. In AI, 2023 was the year people became aware of generative. That technology isnt new, however, and has been simmering for quite some time. AI has been deployed in a variety of other fields for quite a while.
Quantum simulation could be really important in the next year. Are we going to achieve a error-resistant, gate-based quantum computer next year? No. Thats further down the road. There are very interesting near-term applications in quantum simulation or analog quantum computation that I do think will have a significant impact in 2024, even while were waiting for continued advancements in error-correction, gate-based digital quantum computers.
PE: Can you discuss digital twins in quantum computing?
Huestis: Digital twin is a catch all phrase regarding the simulation of a patient or a process. It meshes really nicely with the idea of quantum simulation. Its the idea that in the absence of being able to perform direct measurements of a slew of compounds, we can do some quantum simulation that illuminates the molecular properties of compounds of interest very rapidly.
In that respect, I suppose that quantum simulation is kind of a form of digital twin. More generally, I dont think quantum computing is that suited to the kinds of broader applications that come to mind, such as looking at patient data, hospital systems, or those sorts of things in a broad way. It turns out that classical computing and conventional AI models work really well for that kind of thing.
But for anything that has a quantum element, digital twinning speaks to the strength of quantum computation as a platform.
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How Quantum Computing Trends Will Impact Pharma in 2024: Q&A With Erik Huestis, Partner at Foley Hoag - Pharmaceutical Executive
Quantum computing progress hindered by noise – ReadWrite
Over the past two decades, numerous businesses such as Google, Microsoft, and IBM have joined the race to develop quantum computing. Investors have contributed well over $5 billion towards the ultimate goal of creating the next major innovation. Quantum computers utilize the unusual rules of atomic and subatomic matter to process data in ways unattainable by traditional or classical computers. This technology could revolutionize industries like drug development, cryptography, finance, and supply chain management.
However, the primary challenge hampering the progress of quantum computing is the issue of noise and decoherence, which lead to errors in computations. Qubits, the fundamental unit of quantum computing, are highly sensitive to their environment, and any disturbance or fluctuations in temperature can cause them to lose their quantum state, affecting the accuracy and reliability of calculations.
Despite the potential of quantum computing, it remains fragile and susceptible to even the slightest disturbance, such as a stray photon produced by heat, an accidental signal from nearby electronics, or a physical vibration. This noise causes chaos, leading to errors or even bringing quantum computation to a halt. Scientists and researchers are diligently working on ways to mitigate this issue, utilizing strategies like error correction algorithms, better materials, and improved isolation techniques. The race towards a truly functional and efficient quantum computer hinges on finding the perfect balance between inherent fragility and maintaining performance capabilities.
Researchers believed they might have to work with noisy components. Many sought applications that would still be practical with limited capacity. Although this search has not been particularly successful, recent theoretical and experimental advancements have given researchers hope that noise issues might finally be tackled. These advancements include developing innovative error-correcting techniques and refining hardware designs to minimize interference, driving renewed optimism within the scientific community.
Sabrina Maniscalco, a professor at the University of Helsinki studying the impact of noise on computations, admitted that a decade ago, she dismissed quantum computing due to fundamental issues. However, technological advancements and innovative research around quantum computing began addressing these challenges, changing her perspective and revealing its immense potential to transform industries and solve complex problems.
A mix of hardware and software techniques shows potential in reducing, managing, and correcting quantum errors, aiming to enhance stability and improve overall performance. Researchers are making significant strides toward achieving fault-tolerant quantum computing by combining advanced algorithms with robust hardware designs.
Featured Image Credit: Photo by Markus Winkler; Pexels
Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.
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Quantum computing progress hindered by noise - ReadWrite