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A quantum computer is a computer design which uses the principles of quantum physics to increase the computational power beyond what is attainable by a traditional computer. Quantum computers have been built on a small scale and work continues to upgrade them to more practical models.

Computers function by storing data in a binary number format, which result in a series of 1s & 0s retained in electronic components such as transistors. Each component of computer memory is called a bit and can be manipulated through the steps of Boolean logic so that the bits change, based upon the algorithms applied by the computer program, between the 1 and 0 modes (sometimes referred to as "on" and "off").

A quantum computer, on the other hand, would store information as either a 1, 0, or a quantum superposition of the two states. Such a "quantum bit" allows for far greater flexibility than the binary system.

Specifically, a quantum computer would be able to perform calculations on a far greater order of magnitude than traditional computers ... a concept which has serious concerns and applications in the realm of cryptography & encryption. Some fear that a successful & practical quantum computer would devastate the world's financial system by ripping through their computer security encryptions, which are based on factoring large numbers that literally cannot be cracked by traditional computers within the lifespan of the universe. A quantum computer, on the other hand, could factor the numbers in a reasonable period of time.

To understand how this speeds things up, consider this example. If the qubit is in a superposition of the 1 state and the 0 state, and it performed a calculation with another qubit in the same superposition, then one calculation actually obtains 4 results: a 1/1 result, a 1/0 result, a 0/1 result, and a 0/0 result. This is a result of the mathematics applied to a quantum system when in a state of decoherence, which lasts while it is in a superposition of states until it collapses down into one state. The ability of a quantum computer to perform multiple computations simultaneously (or in parallel, in computer terms) is called quantum parallelism.

The exact physical mechanism at work within the quantum computer is somewhat theoretically complex and intuitively disturbing. Generally, it is explained in terms of the multi-world interpretation of quantum physics, wherein the computer performs calculations not only in our universe but also in other universes simultaneously, while the various qubits are in a state of quantum decoherence. While this sounds far-fetched, the multi-world interpretation has been shown to make predictions which match experimental results.

Quantum computing tends to trace its roots back to a 1959 speech by Richard P. Feynman in which he spoke about the effects of miniaturization, including the idea of exploiting quantum effects to create more powerful computers. This speech is also generally considered the starting point of nanotechnology.

Of course, before the quantum effects of computing could be realized, scientists and engineers had to more fully develop the technology of traditional computers. This is why, for many years, there was little direct progress, nor even interest, in the idea of making Feynman's suggestions into reality.

In 1985, the idea of "quantum logic gates" was put forth by the University of Oxford's David Deutsch, as a means of harnessing the quantum realm inside a computer. In fact, Deutsch's paper on the subject showed that any physical process could be modeled by a quantum computer.

Nearly a decade later, in 1994, AT&T's Peter Shor devised an algorithm that could use only 6 qubits to perform some basic factorizations ... more cubits the more complex the numbers requiring factorization became, of course.

A handful of quantum computers has been built. The first, a 2-qubit quantum computer in 1998, could perform trivial calculations before losing decoherence after a few nanoseconds. In 2000, teams successfully built both a 4-qubit and a 7-qubit quantum computer. Research on the subject is still very active, although some physicists and engineers express concerns over the difficulties involved in upscaling these experiments to full-scale computing systems. Still, the success of these initial steps does show that the fundamental theory is sound.

The quantum computer's main drawback is the same as its strength: quantum decoherence. The qubit calculations are performed while the quantum wave function is in a state of superposition between states, which is what allows it to perform the calculations using both 1 & 0 states simultaneously.

However, when a measurement of any type is made to a quantum system, decoherence breaks down and the wave function collapses into a single state. Therefore, the computer has to somehow continue making these calculations without having any measurements made until the proper time, when it can then drop out of the quantum state, have a measurement taken to read its result, which then gets passed on to the rest of the system.

The physical requirements of manipulating a system on this scale are considerable, touching on the realms of superconductors, nanotechnology, and quantum electronics, as well as others. Each of these is itself a sophisticated field which is still being fully developed, so trying to merge them all together into a functional quantum computer is a task which I don't particularly envy anyone ... except for the person who finally succeeds.

Excerpt from:
How Quantum Computers Work

Among the healthcare technologies venture firms be looking at most closely at in 2020, various artificial intelligence and machine learning applications are atop this list, of course. But so are more nuts-and-bolts tools like administrative process automation and patient engagement platforms, VCs say.

Other, more leading-edge technologies genomics-focused data and analytics, and even quantum computing are among the areas attracting investor interest this year.

"We expect 2020 to mark the first year where health IT venture firms will start to look at quantum computing technology for upcoming solutions," Dr. Anis Uzzaman, CEO and general partner of Pegasus Tech Ventures, told Healthcare IT News.

"With the breakthrough supremacy announcement from Google validating the technology and the subsequent launch of the service Amazon Braket in 2019, there is sure to be a new wave of entrepreneurial activity starting in 2020."

He said quantum computing technology holds a lot of promise for the healthcare industry with potential breakthroughs possible throughout the health IT stack from operations and administration to security.

Among the promising companies, Uzzaman pointed to Palo Alto-based QC Ware, a startup pioneering a software solution that enables companies to use a variety of quantum hardware platforms such as Rigetti and IBM to solve a variety of enterprise problems, including those specifically related to healthcare.

He also predicted artificial intelligence would continue to be at the forefront for health IT venture firms in 2020 as it becomes more clear which startups may be winners in their initial target sectors.

"There has been consistent growth of investment activity over the past few years into healthcare startups using artificial intelligence to target a range of areas from imaging to diagnostics," he said.

However, Uzzaman also noted regulation and long enterprise sales cycles have largely slowed the ability for these companies to significantly scale their revenues.

"Therefore, we anticipate 2020 will be the year where it will become clearer to health IT venture firms who will be winners in applying artificial intelligence to imaging, pathology, genomics, operations, diagnostics, transcription, and more," he said. "We will also continue to see moderate growth in the overall investment amount in machine learning and AI companies, but will see a notable decrease in the number of companies receiving an investment.

Uzzaman explained there were already some signs in late 2019 that there could be late in a short-term innovation cycle for artificial intelligence with many companies, particularly those applying machine learning and AI to robotics, shutting down.

"However, we anticipate many companies will reach greater scale with their solutions and separate themselves from the competition, which will translate into more mega funding rounds," he said.

Ezra Mehlman, managing partner with Health Enterprise Partners, explained that at the beginning of each year, the firm conducts a market mapping exercise to determine which healthcare IT categories are rising to the top of the prioritization queue of its network of hospital and health plan limited partners.

"In the past year, we have seen budgets meaningfully open for automation solutions in administrative processing, genomics-focused data and analytics offerings, aging-in-place technologies and, in particular, patient engagement platforms rooted in proven clinical use cases," he said. "We are actively looking at all of these spaces."

He pointed out that in 2018, more than $2 billion was invested into artificial intelligence and machine learning healthcare IT companies, which represented a quarter of the total dollars invested into digital health companies that year.

"We view this as a recognition of two things: the meteoric aspirations that the market has assigned to AI and machine learning's potential, and a general sense that the underlying healthcare data infrastructure has reached the point of maturity, where it is possible to realize ROI from AI/machine learning initiatives," he said.

However, he said Health Enterprise Partners is still waiting for the "breakout" to occur in adoption.

"We believe we have now reached the point where category leaders will emerge in each major healthcare AI subsector and the usage will become more widespread we have made one such investment in the clinical AI space in the last year," Mehlman said.

Heading into 2020, Mehlman said companies that cannot deliver high-six-figure, year-one ROI in the form of increased revenue or reduced cost will struggle, and companies that cannot crisply answer the question, "Who is the buyer and what is the budget?" will be challenged.

"If one applies these tests to some of the areas that have attracted the most healthcare VC investment--social determinants of health, blockchain and digital therapeutics to name a few the number of viable companies sharply drops off," he said.

Mehlman noted that while these sound like simple principles, the current environment of rapidly consolidating, budget-constrained hospitals, vertically integrating health plans, and big tech companies making inroads into healthcare has raised the bar on what is required for a healthcare startup to gain meaningful market traction.

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Healthcare venture investment in 2020: Quantum computing gets a closer look - Healthcare IT News

BEIJING, Jan. 21, 2020 The 2020 ASC Student Supercomputer Challenge (ASC20) announced the tasks for the new season: using supercomputers to simulate Quantum circuit and training AI models to take English test. These tasks can be unprecedented challenges for the 300+ ASC teams from around the world. From April 25 to 29, 2020, top 20 finalists will fiercely compete at SUSTech in Shenzhen, China.

ASC20 set up Quantum Computing tasks for the first time. Teams are going to use the QuEST (Quantum Exact Simulation Toolkit) running on supercomputers to simulate 30 qubits in two cases: quantum random circuits (random.c), and quantum fast Fourier transform circuits (GHZ_QFT.c). Quantum computing is a disruptive technology, considered to be the next generation high performance computing. However the R&D of quantum computers is lagging behind due to the unique properties of quantum. It adds extra difficulties for scientists to use real quantum computers to solve some of the most pressing problems such as particle physics modeling, cryptography, genetic engineering, and quantum machine learning. From this perspective, the quantum computing task presented in the ASC20 challenge, hopefully, will inspire new algorithms and architectures in this field.

The other task revealed is Language Exam Challenge. Teams will take on the challenge to train AI models on an English Cloze Test dataset, vying to achieve the highest test scores. The dataset covers multiple levels of English language tests in China, including the college entrance examination, College English Test Band 4 and Band 6, and others. Teaching the machines to understand human language is one of the most elusive and long-standing challenges in the field of AI. The ASC20 AI task signifies such a challenge, by using human-oriented problems to evaluate the performance of neural networks.

Wang Endong, ASC Challenge initiator, member of the Chinese Academy of Engineering and Chief Scientist at Inspur Group, said that through these tasks, students from all over the world get to access and learn the most cutting-edge computing technologies. ASC strives to foster supercomputing & AI talents of global vision, inspiring technical innovation.

Dr. Lu Chun, Vice President of SUSTech host of the ASC20 Finals, commented that supercomputers are important infrastructure for scientific innovation and economic development. SUSTech makes focused efforts on developing supercomputing and hosting ASC20, hoping to drive the training of supercomputing talent, international exchange and cooperation, as well as inter discipline development at SUSTech.

Furthermore, during January 15-16, 2020, the ASC20 organizing committee held a competition training camp in Beijing to help student teams prepare for the ongoing competition. HPC and AI experts from the State Key Laboratory of High-end Server and Storage Technology, Inspur, Intel, NVIDIA, Mellanox, Peng Cheng Laboratory and the Institute of Acoustics of the Chinese Academy of Sciences gathered to provide on-site coaching and guidance. Previous ASC winning teams also shared their successful experiences.

About ASC

The ASC Student Supercomputer Challenge is the worlds largest student supercomputer competition, sponsored and organized by Asia Supercomputer Community in China and supported by Asian, European, and American experts and institutions. The main objectives of ASC are to encourage exchange and training of young supercomputing talent from different countries, improve supercomputing applications and R&D capacity, boost the development of supercomputing, and promote technical and industrial innovation. The annual ASC Supercomputer Challenge was first held in 2012 and has since attracted over 8,500 undergraduates from all over the world. Learn more ASC athttps://www.asc-events.org/.

Source: ASC

The rest is here:
ASC20 Finals to be Held in Shenzhen, Tasks Include Quantum Computing Simulation and AI Language Exam - HPCwire

The world of quantum is the world of the very, very small. At sizes near those of atoms and smaller, the rules of physics start morphing into something unrecognizableat least to us in the regular world. While quantum physics seems bizarre, it offers huge opportunities.

Quantum physics may hold the key to vast technological improvements in computing, sensing, and communication. Quantum computing may be able to solve problems in minutes that would take lifetimes on todays computers. Quantum sensors could act as extremely high-powered antennas for the military. Quantum communication systems could be nearly unhackable. But we dont have the knowledge or capacity to take advantage of these benefitsyet.

The Department of Energy (DOE) recently announced that it will establish Quantum Information Science Centers to help lay the foundation for these technologies. As Congress put forth in the National Quantum Initiative Act, the DOEs Office of Science will make awards for at least two and up to five centers.

These centers will draw on both quantum physics and information theory to give us a soup-to-nuts understanding of quantum systems. Teams of researchers from universities, DOE national laboratories, and private companies will run them. Their expertise in quantum theory, technology development, and engineering will help each center undertake major, cross-cutting challenges. The centers work will range from discovery research up to developing prototypes. Theyll also address a number of different technical areas. Each center must tackle at least two of these subjects: quantum communication, quantum computing and emulation, quantum devices and sensors, materials and chemistry for quantum systems, and quantum foundries for synthesis, fabrication, and integration.

The impacts wont stop at the centers themselves. Each center will have a plan in place to transfer technologies to industry or other research partners. Theyll also work to leverage DOEs existing facilities and collaborate with non-DOE projects.

As the nations largest supporter of basic research in the physical sciences, the Office of Science is thrilled to head this initiative. Although quantum physics depends on the behavior of very small things, the Quantum Information Science Centers will be a very big deal.

The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, please visit https://www.energy.gov/science.

Read more:
New Centers Lead the Way towards a Quantum Future - Energy.gov

Something to look forward to: Some of the biggest problems that need solving in the enterprise world require sifting through vast amounts of data and finding the best possible solution given a number of factors and requirements, some of which are at times unknown. For years, quantum computing has been touted as the most promising jump in computational speed for certain kind of problems, but Toshiba says revisiting classical algorithms helped it develop a new one that can leverage existing silicon-based hardware to get a faster result.

Toshiba's announcement this week claims a new algorithm it's been perfecting for years is capable of analyzing market data much more quickly and efficiently than those used in some of the world's fastest supercomputers.

The algorithm is called the "Simulated Bifurcation Algorithm," and is supposedly good enough to be used in finding accurate approximate solutions for large-scale combinatorial optimization problems. In simpler terms, it can come up with a solution out of many possible ones for a particularly complex problem.

According to its inventor, Hayato Goto, it draws inspiration from the way quantum computers can efficiently comb through many possibilities. Work on SBA started in 2015, and Goto noticed that adding new inputs to a complex system with 100,000 variables makes it easy to solve it in a matter of seconds with a relatively small computational cost.

This essentially means that Toshiba's new algorithm could be used on standard desktop computers. To give you an idea how important this development is, Toshiba demonstrated last year that SBA can get highly accurate solutions for an optimization problem with 2,000 connected variables in 50 microseconds, or 10 times faster than laser-based quantum computers.

SBA is also highly scalable, meaning it can be made to work on clusters of CPUs or FPGAs, all thanks to the contributions of Kosuke Tatsumura, another one of Toshiba's senior researchers that specializes in semiconductors.

Companies like Microsoft, Google, IBM, and many others are racing to be the first with a truly viable quantum commercial system, but so far their approaches have produced limited results that live inside their labs.

Meanwhile, scientists like Goto and Kosuke are going back to the roots by exploring ways to improve on classical algorithms. Toshiba hopes to use SBA to optimize financial operations like currency trading and rapid-fire portfolio adjustments, but this could very well be used to calculate efficient routes for delivery services and molecular precision drug development.

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Toshiba says it created an algorithm that beats quantum computers using standard hardware - TechSpot