Category Archives: Quantum Computing

BOULDER, Colo., Oct. 18, 2021 /PRNewswire/ --ColdQuanta, the leader in Cold Atom Quantum Technology, today announced the company has embarked on its first project under the newly branded Quantum Research as a Service (QRaaS) Division to build a Custom Ion Trap System for Oak Ridge National Labs (ORNL). The QRaaS division sits alongside the company's Quantum Computing and Cold Atom Technology groups, and is dedicated to discovering breakthrough technology in support of government and enterprises. The Oak Ridge system will apply thoughtful engineering to create a high performance and modular system that enables rapid testing of cryogenic electronics, ion trap architectures, and system integration strategies. The cryogenic ion trapping system combines the modular design and systems engineering that ColdQuanta has demonstrated in several of its products to produce a reliable system that is tailored to the customer's needs for testing and prototyping ion trap hardware.

In recent years, ion traps have been increasingly integrated into cryogenic systems to achieve improved vacuum performance and decreased noise. Trapped ion experiments typically require bulky, one-off vacuum systems, and cryogenic experiments add yet another layer of complexity that requires more expertise and time for system design and construction. ColdQuanta's ion trapping system addresses these challenges by including a macroscopic vacuum chamber with integrated electronics, active and passive vacuum pumping mechanisms, an atomic source, thermal links, a compact helical resonator, and trapping electronics all contained within the cryostation chamber.

The cryogenic ion trapping systems fuels quantum adoption in the following ways:

"ORNL's cryogenic ion trapping systems is the perfect type of project for ColdQuanta's Quantum Research as a Service division because it furthers adoption of quantum in familiar areas like computing, networking, and simulation," said Max Perez, general manager, Quantum Research as a Service, at ColdQuanta. "Our mission at ColdQuanta is to show how accessible quantum can be at making everyday applications better, faster and more efficient. We're pleased that ORNL selected us to help bring this mission to life through the cryogenic ion trapping system."

About ColdQuantaColdQuanta is the leader in Cold Atom Quantum Technology, the most scalable, versatile, and commercially viable application of quantum. The company operates three lines of business - Quantum Computing, Devices and Machines, and Quantum Research-as-a-Service. The Quantum Computing division is developing the launch of Hilbert 1.0, a cloud-based 100 qubit quantum computer. The Devices and Machines division provides products for quantum computing companies and quantum lab environments. Quantum Research-as-a-Service supports the government and enterprises in developing quantum inertial sensing, radio frequency receivers, and networking technologies, including high precision clock prototypes. ColdQuanta is based in Boulder, CO, with offices in Madison, Wisconsin and Oxford, UK. Find out more at http://www.coldquanta.com.

The name ColdQuanta and the ColdQuanta logo are both registered trademarks of ColdQuanta, Inc.

SOURCE ColdQuanta, Inc.

http://www.coldquanta.com

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ColdQuanta's Newly Formed Research as a Service Division Embarks on First Project with Oak Ridge National Labs - PRNewswire

TOKYO--(BUSINESS WIRE)--Sumitomo Corporation Quantum Transformation Project (hereinafter referred to as "QX PJ"), which aims to revolutionize society with the power of quantum computers, is collaborating with OneSky, a provider of unmanned traffic management (UTM) solutions, and Tohoku University, which has extensive research experience in quantum annealing, a method specializing in optimization among quantum computing. The QX PJ has conducted a demonstration of the use of quantum computing to develop a real-time three-dimensional traffic control system for the era when hundreds of thousands of air mobility vehicles will be flying in the sky, and has improved the number of flying vehicles that can fly simultaneously by about 70%. We have also demonstrated that quantum computing is about 10 times faster than conventional computers in certain problems. In the future, we believe that quantum computers will be able to increase the number of flying cars by further improving their performance, and that air mobility will be able to create new value by providing the shortest and best route for emergency flights that should be prioritized.

Air mobility is a next generation means of transportation that is expected to shorten travel time in urban areas, improve convenience of travel in remote islands and mountainous areas, and speed up emergency transport and goods transportation. To ensure the safety and security of air traffic in the age of air mobility, it is necessary to determine the optimal flight operation considering the ever-changing weather, radio wave conditions, and the situation of other air mobiles. However, it may be difficult for conventional computers to find the answer in real time from an exponentially increasing number of combinations. To solve this problem, QX PJ has started a quantum technology demonstration to control a large number of air mobilities in real time.

The results of the demonstration experiment are now available on video. Please see the video.URL: https://www.youtube.com/watch?v=bv5viYQQ8Lw

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Sumitomo Corporation Quantum Transformation (QX) Project - Quantum Computer Improves Performance of Traffic Control for Flying Cars, One Step Closer...

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ColdQuanta's Newly Formed Research as a Service Division Embarks on First Project with Oak Ridge National Labs - The Grand Junction Daily Sentinel

Oct. 19, 2021 Three Chicago Quantum Exchange Members have received distinguished awards from the American PhysicalSociety (APS)for their work in quantum science, including work in spin transport, theoretical quantum information science, and theoretical methods to compute and engineer the electronic and structural properties of molecules and materials.

Axel Hoffmann, at member instituteUniversity of Illinois at Urbana-Champaign, received the 2022 David Adler Lectureship Award in the Field of Material Physics for his work advancing the understanding of spin transport and magnetization dynamics in magnetic multilayers.He is also being recognized for his inspiring lectures and engaging discussions.

AtThe University of Chicago,Liang Jiangreceived the 2022 Rolf Landauer and Charles H. Bennett Award in Quantum Computing for his contributions tothe field of theoretical quantum information science. His research focusses on exploiting novel error correction strategies to enhance performance in a manner compatible with state-of-the-art experimental platforms, and for helping establish new foundations for fault-tolerant and practical quantum communication, computing, and sensing.

The third CQE recipient to win an award from APS isGiulia Galli,aLiew Family professorof Electronic Structure and Simulations in thePritzker School of Molecular EngineeringandProfessor of Chemistryat the University of Chicago. Giulia Galli is also a Senior Scientist atArgonne National Lab(ANL). Galli received the 2022 Aneesur Rahman Prize for Computational Physics for her work to develop theoretical methods to compute and engineer the electronic and structural properties of molecules and materials. Her work broadens the applicability of first-principles computational approaches to multiple disciplines.

About the American PhysicalSociety (APS) Awards:

TheAPS Prizes and Awardsrecognize outstanding achievements in research, education, and public service. With few exceptions, they are open to all members of the scientific community in the US and abroad. The nomination and selection procedure, involving APS-appointed selection committees, guarantees high standards and prestige.

APS announced the Societys Spring 2022 prize and award recipients, including those for the 2021 LeRoy Apker Award for undergraduate research, the 2021 Dwight Nicholson Medal for Outreach, and the 2021 Stanford R. Ovshinsky Sustainable Energy Fellowship, on October 15, 2021.

View the story on UIUCs website

View the story on PMEs website

View the full list of recipients

Source: Chicago Quantum Exchange

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3 CQE members Receive Awards from the American Physical Society - HPCwire

NEW YORK, Oct. 19, 2021 /PRNewswire/ --3DR Holdings today announced a deep dive into Quantum Safe initiatives and use cases as a prime focus of Inside Quantum Technology, the industry's leading conference and exhibition. Sponsored by IBM, Inside Quantum Technology will run from November 1-5 as a hybrid virtual and in-person event with live sessions in New York City. The conference is dedicated to the business of quantum computing and will feature presentations and discussions critical to those seeking new business revenues from quantum-related opportunities.

Continued developments in quantum computing represent a serious threat to existing encryption systems that protect critical networks and applications. It's against this backdrop that Inside Quantum Technology will focus on technologies being developed to protect these systems, along with an examination of real-world end use cases.

In addition to its world-class conference program, Inside Quantum Technology will provide attendees with opportunities to visit leading vendors in its exhibit hall, both in-person and virtually, where visitors can download materials, watch videos, and connect with company representatives. The event also offers networking opportunities on each day, enabling participants to gather and engage based on specific quantum-related topics.

For additional details about Inside Quantum Technology, including the complete agenda, registration information, sponsorship and exhibition options, please visit https://iqtevent.com/fall/.

About 3DR Holdings3DR Holdings is a technology media organization with website, research and international trade show interests in the fields of Quantum Technology and 3D Printing. For more information, please visit https://3drholdings.com.

About Inside Quantum TechnologyInside Quantum Technology is the only organization worldwide dedicated to meeting the strategic information and analysis needs of the emerging quantum technology sector via events, daily news, research and podcasts. For additional information, please visit https://www.insidequantumtechnology.com.

Media Contact: Barry Schwartz, Schwartz Public Relations[emailprotected], 212-677-8700 ext. 118

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INSIDE QUANTUM TECHNOLOGY New York, The Largest Business Quantum Technology Conference and Exhibition, Announces Focus on Quantum Safe Initiatives and...

Quantum Computing in Health Care Market report focused on the comprehensive analysis of current and future prospects of the Quantum Computing in Health Care industry. It describes the optimal or favourable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth during a forecast period.

An in-depth analysis of past trends, future trends, demographics, technological advancements, and regulatory requirements for the Quantum Computing in Health Care market has been done in order to calculate the growth rates for each segment and sub-segments.

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Note In order to provide more accurate market forecast, all our reports will be updated before delivery by considering the impact of COVID-19.

Top Key Vendors of this Market are:

D-Wave Solutions, IBM, Google, Microsoft, Rigetti Computing, Intel, Anyon Systems Inc., Cambridge Quantum Computing Limited, Origin Quantum Computing Technology.

Global Quantum Computing in Health Care Market Segmentation:

Product Type Segmentation:

Diagnostic AssistancePrecision MedicineOthers

Industry Segmentation:

HospitalResearch InstituteOther

Various factors are responsible for the markets growth trajectory, which are studied at length in the report. In addition, the report lists down the restraints that are posing threat to the global Quantum Computing in Health Care market. This report is a consolidation of primary and secondary research, which provides market size, share, dynamics, and forecast for various segments and sub-segments considering the macro and micro environmental factors. It also gauges the bargaining power of suppliers and buyers, threat from new entrants and product substitute, and the degree of competition prevailing in the market.

The influence of the latest government guidelines is also analysed in detail in the report. It studies the Quantum Computing in Health Care markets trajectory between forecast periods. The cost analysis of the Global Quantum Computing in Health Care Market has been performed while keeping in view manufacturing expenses, labour cost, and raw materials and their market concentration rate, suppliers, and price trend.

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The report provides insights on the following pointers:

Market Penetration: Comprehensive information on the product portfolios of the top players in the Quantum Computing in Health Care market.

Competitive Assessment: In-depth assessment of the market strategies, geographic and business segments of the leading players in the market.

Product Development/Innovation: Detailed insights on the upcoming technologies, R&D activities, and product launches in the market.

Market Development: Comprehensive information about emerging markets. This report analyzes the market for various segments across geographies.

Market Diversification: Exhaustive information about new products, untapped geographies, recent developments, and investments in the Quantum Computing in Health Care market.

Regions Covered in the Global Quantum Computing in Health Care Market Report 2021: The Middle East and Africa (GCC Countries and Egypt) North America (the United States, Mexico, and Canada) South America (Brazil etc.) Europe (Turkey, Germany, Russia UK, Italy, France, etc.) Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)

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Table of Contents

Global Quantum Computing in Health Care Market Research Report 2021 2027

Chapter 1 Quantum Computing in Health Care Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Quantum Computing in Health Care Market Forecast

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Incredible Growth of Quantum Computing in Health Care Market by 2028 | D-Wave Solutions, IBM, Google EcoChunk - EcoChunk

Two UC Santa Barbara graduate students in the College of Engineering have received opportunities to conduct research at prestigious national laboratories operated by the U.S. Department of Energy (DOE). Eli Zoghlin and Kamyar Parto are among 65 students nationwide selected to participate in the DOEs Office of Science Graduate Student Research (SCGSR) program. The fellowship provides funding to the awardees as they collaborate with established scientists at one of the agencys fourteen national laboratories.

Zoghlin, a sixth-year materials Ph.D. student who is advised by materials professor Stephen Wilson, investigates crystal growth and the characterization of fundamentally interesting magnetic and electronic materials. He will work with Matt Stone, who operates an instrument called SEQUOIA in the Spallation Neutron Source (SNS) at the Oak Ridge National Laboratory (ORNL) in Tennessee.

Academically, this fellowship could not have come at a better time, said Zoghlin, who plans to complete his doctoral degree next fall. Working with Matt Stone, who is an expert in neutron scattering, is a fantastic opportunity for me to improve my mastery of a technique that can only be carried out at dedicated facilities like ORNL. While a lot can be learned from books, there is nothing like hands-on experience to truly learn how to carry out an experiment.

During the height of the pandemic, travel restrictions limited opportunities for outside researchers to conduct high-value experiments at national labs, and as a result, delayed collection of data central for publications.

This DOE fellowship provides me the opportunity to make up for that and work directly with Matt on my own experiment and others, added Zoghlin, who received a bachelors degree in materials science and engineering from Carnegie Mellon University. I hope to carry out several publishable experiments to complete my last project as a graduate student and begin writing my thesis.

His research project, Study of the Structure and Dynamics of Li2TMO2 (TM = Cu, Ni) via Neutron Scattering, will investigate two magnetic materials, dilithium copper oxygen (Li2CuO2) and dilithium nickel oxygen (Li2NiO2). These materials are structurally very similar meaning their periodic arrangement of atoms is the same with both having one-dimensional chains of copper (Cu)/nickel (Ni) ions that are well separated from each other. The difference between the materials lies in the intrinsic magnetic properties of Cu and Ni, which is what Zoghlin plans to investigate. He will take materials that he is currently synthesizing in the Wilson lab to the SNS, where he will use the neutrons produced there for his research project. Neutrons, the subatomic particle found in the nucleus of all atoms, interact with magnetic materials in well-defined ways and, with a technique known as neutron scattering, can be used to understand certain properties.

By studying how neutrons scatter off the two materials, I will learn what type of magnetic order they each show and how the interactions between the Cu/Ni atoms lead to that order, explained Zoghlin, who is scheduled to conduct his research at the national lab for three months, starting in January 2022. This is fundamental research at its finest.

Parto, a third-year electrical and computer engineering Ph.D. student, was selected to study quantum light sources, an important step in the push to design small and scalable quantum computers that function at room temperatures. Co-advised by electrical and computer engineering faculty members Kaustav Banerjee and Galan Moody, Parto will work with Han Htoon in the Center for Integrated Nanotechnologies (CINT) at the Los Alamos National Laboratory in New Mexico.

Dr. Htoon is one of the pioneers in this field, and his expertise, combined with the state-of-the-art implantation facilities, provide an ideal setting for a researcher, said Parto, who joined the Ph.D. program after completing the masters program at UCSB. The journey of my Ph.D. has been filled with periods of self-doubt and questioning of my own methods, but this recognition has provided an immeasurable morale and motivational boost.

Parto studies and characterizes defect complexes in transition metal dichalcogenides (TMDs) for application in quantum light generation and quantum computing. TMDs are two-dimensional (2D), atomically thin materials that show unique electrical, mechanical and optical properties. TMDs can contain a number of structural defects in their crystal lattices, which significantly alter their properties. Studying defects allows researchers to eliminate unfavorable defects and introduce beneficial ones to realize higher-performing materials and technologies.

Recently, researchers learned that some structural imperfections in TMDs can be triggered to emit a single photon, one at a time. This type of light, called quantum light, is a vital building block for quantum photonics circuits. For his project, Engineering and Characterization of Quantum Defects in 2D TMDs, Parto will engineer these defects at the atomic level and characterize their quantum light emission.

My work aims to address one of the major bottlenecks in the field by finding the right quantum light source that can be integrated with the current photonics technology platform, explained Parto, who received his bachelors degree in engineering science - electronics with a minor in computational sciences from the University of Tehran, Iran.

Results from his project could lead to the development and application of efficient and scalable sources of quantum light.

The DOE selected projects that strongly align with priority mission areas of the Office of Science that have a high need for workforce development. The program is intended to strengthen the pipeline for developing a highly skilled scientific and technological workforce by providing new graduate research opportunities at DOE national laboratories. Since 2014, the SCGSR program has provided supplemental funding to nearly 800 U.S. graduate awardees from 153.

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Priority Projects | The UCSB Current - The UCSB Current

emerging technologies built on quantum mechanics

Quantum technology is an emerging field of physics and engineering, which relies on the principles of quantum physics.[1] Quantum computing, quantum sensors, quantum cryptography, quantum simulation, quantum metrology and quantum imaging are all examples of quantum technologies, where properties of quantum mechanics, especially quantum entanglement, quantum superposition and quantum tunnelling, are important.

Quantum secure communication are methods which are expected to be 'quantum safe' in the advent of a quantum computing systems that could break current cryptography systems. One significant component of a quantum secure communication systems is expected to be Quantum key distribution, or 'QKD': a method of transmitting information using entangled light in a way that makes any interception of the transmission obvious to the user. Another technology in this field is the quantum random number generator used to protect data. This produces truly random numbers without following the procedure of the computing algorithms that merely imitate randomness.[2]

Quantum computers are expected to have a number of important uses in computing fields such as optimization and machine learning. They are perhaps best known for their expected ability to carry out 'Shor's Algorithm', which can be used to factorise large numbers and is an important process in the securing of data transmissions.

There are many devices available today which are fundamentally reliant on the effects of quantum mechanics. These include laser systems, transistors and semiconductor devices and other devices, such as MRI imagers. The UK Defence Science and Technology Laboratory (DSTL) grouped these devices as 'quantum 1.0',[3] that is devices which rely on the effects of quantum mechanics. These are generally regarded as a class of device that actively create, manipulate and read out quantum states of matter, often using the quantum effects of superposition and entanglement.

The field of quantum technology was first outlined in a 1997 book by Gerard J. Milburn,[4] which was then followed by a 2003 article by Jonathan P. Dowling and Gerard J. Milburn,[5][6] as well as a 2003 article by David Deutsch.[7] The field of quantum technology has benefited immensely from the influx of new ideas from the field of quantum information processing, particularly quantum computing. Disparate areas of quantum physics, such as quantum optics, atom optics, quantum electronics, and quantum nanomechanical devices, have been unified in the search for a quantum computer and given a common "language", that of quantum information theory.

From 2010 onwards, multiple governments have established programmes to explore quantum technologies,[8] such as the UK National Quantum Technologies Programme,[9] which created four quantum 'hubs', the Centre for Quantum Technologies in Singapore, and QuTech, a Dutch centre to develop a topological quantum computer.[10] In 2016, the European Union introduced the Quantum Technology Flagship,[11][12] a 1 Billion, 10-year-long megaproject, similar in size to earlier European Future and Emerging Technologies Flagship projects.[13][14] In December 2018, the United States passed the National Quantum Initiative Act, which provides a US$1 billion annual budget for quantum research.[15] China is building the world's largest quantum research facility with a planned investment of 76 Billion Yuan (approx. 10 Billion).[16][17]

In the private sector, large companies have made multiple investments in quantum technologies. Examples include Google's partnership with the John Martinis group at UCSB,[18] multiple partnerships with the Canadian quantum computing company D-wave systems, and investment by many UK companies within the UK quantum technologies programme.

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Quantum technology - Wikipedia

Quantum computing is all the rage. It seems like hardly a day goes by without some news outlet describing the extraordinary things this technology promises. Most commentators forget, or just gloss over, the fact that people have been working on quantum computing for decadesand without any practical results to show for it.

We've been told that quantum computers could provide breakthroughs in many disciplines, including materials and drug discovery, the optimization of complex systems, and artificial intelligence." We've been assured that quantum computers will forever alter our economic, industrial, academic, and societal landscape." We've even been told that the encryption that protects the world's most sensitive data may soon be broken" by quantum computers. It has gotten to the point where many researchers in various fields of physics feel obliged to justify whatever work they are doing by claiming that it has some relevance to quantum computing.

Meanwhile, government research agencies, academic departments (many of them funded by government agencies), and corporate laboratories are spending billions of dollars a year developing quantum computers. On Wall Street, Morgan Stanley and other financial giants expect quantum computing to mature soon and are keen to figure out how this technology can help them.

It's become something of a self-perpetuating arms race, with many organizations seemingly staying in the race if only to avoid being left behind. Some of the world's top technical talent, at places like Google, IBM, and Microsoft, are working hard, and with lavish resources in state-of-the-art laboratories, to realize their vision of a quantum-computing future.

In light of all this, it's natural to wonder: When will useful quantum computers be constructed? The most optimistic experts estimate it will take 5 to 10 years. More cautious ones predict 20 to 30 years. (Similar predictions have been voiced, by the way, for the last 20 years.) I belong to a tiny minority that answers, Not in the foreseeable future." Having spent decades conducting research in quantum and condensed-matter physics, I've developed my very pessimistic view. It's based on an understanding of the gargantuan technical challenges that would have to be overcome to ever make quantum computing work.

The idea of quantum computing first appeared nearly 40 years ago, in 1980, when the Russian-born mathematician Yuri Manin, who now works at the Max Planck Institute for Mathematics, in Bonn, first put forward the notion, albeit in a rather vague form. The concept really got on the map, though, the following year, when physicist Richard Feynman, at the California Institute of Technology, independently proposed it.

Realizing that computer simulations of quantum systems become impossible to carry out when the system under scrutiny gets too complicated, Feynman advanced the idea that the computer itself should operate in the quantum mode: Nature isn't classical, dammit, and if you want to make a simulation of nature, you'd better make it quantum mechanical, and by golly it's a wonderful problem, because it doesn't look so easy," he opined. A few years later, University of Oxford physicist David Deutsch formally described a general-purpose quantum computer, a quantum analogue of the universal Turing machine.

The subject did not attract much attention, though, until 1994, when mathematician Peter Shor (then at Bell Laboratories and now at MIT) proposed an algorithm for an ideal quantum computer that would allow very large numbers to be factored much faster than could be done on a conventional computer. This outstanding theoretical result triggered an explosion of interest in quantum computing. Many thousands of research papers, mostly theoretical, have since been published on the subject, and they continue to come out at an increasing rate.

The basic idea of quantum computing is to store and process information in a way that is very different from what is done in conventional computers, which are based on classical physics. Boiling down the many details, it's fair to say that conventional computers operate by manipulating a large number of tiny transistors working essentially as on-off switches, which change state between cycles of the computer's clock.

The state of the classical computer at the start of any given clock cycle can therefore be described by a long sequence of bits corresponding physically to the states of individual transistors. With N transistors, there are 2N possible states for the computer to be in. Computation on such a machine fundamentally consists of switching some of its transistors between their on" and off" states, according to a prescribed program.

Illustration: Christian Gralingen

In quantum computing, the classical two-state circuit element (the transistor) is replaced by a quantum element called a quantum bit, or qubit. Like the conventional bit, it also has two basic states. Although a variety of physical objects could reasonably serve as quantum bits, the simplest thing to use is the electron's internal angular momentum, or spin, which has the peculiar quantum property of having only two possible projections on any coordinate axis: +1/2 or 1/2 (in units of the Planck constant). For whatever the chosen axis, you can denote the two basic quantum states of the electron's spin as and .

Here's where things get weird. With the quantum bit, those two states aren't the only ones possible. That's because the spin state of an electron is described by a quantum-mechanical wave function. And that function involves two complex numbers, and (called quantum amplitudes), which, being complex numbers, have real parts and imaginary parts. Those complex numbers, and , each have a certain magnitude, and according to the rules of quantum mechanics, their squared magnitudes must add up to 1.

That's because those two squared magnitudes correspond to the probabilities for the spin of the electron to be in the basic states and when you measure it. And because those are the only outcomes possible, the two associated probabilities must add up to 1. For example, if the probability of finding the electron in the state is 0.6 (60 percent), then the probability of finding it in the state must be 0.4 (40 percent)nothing else would make sense.

In contrast to a classical bit, which can only be in one of its two basic states, a qubit can be in any of a continuum of possible states, as defined by the values of the quantum amplitudes and . This property is often described by the rather mystical and intimidating statement that a qubit can exist simultaneously in both of its and states.

Yes, quantum mechanics often defies intuition. But this concept shouldn't be couched in such perplexing language. Instead, think of a vector positioned in the x-y plane and canted at 45 degrees to the x-axis. Somebody might say that this vector simultaneously points in both the x- and y-directions. That statement is true in some sense, but it's not really a useful description. Describing a qubit as being simultaneously in both and states is, in my view, similarly unhelpful. And yet, it's become almost de rigueur for journalists to describe it as such.

In a system with two qubits, there are 22 or 4 basic states, which can be written (), (), (), and (). Naturally enough, the two qubits can be described by a quantum-mechanical wave function that involves four complex numbers. In the general case of N qubits, the state of the system is described by 2N complex numbers, which are restricted by the condition that their squared magnitudes must all add up to 1.

While a conventional computer with N bits at any given moment must be in one of its 2N possible states, the state of a quantum computer with N qubits is described by the values of the 2N quantum amplitudes, which are continuous parameters (ones that can take on any value, not just a 0 or a 1). This is the origin of the supposed power of the quantum computer, but it is also the reason for its great fragility and vulnerability.

How is information processed in such a machine? That's done by applying certain kinds of transformationsdubbed quantum gates"that change these parameters in a precise and controlled manner.

Experts estimate that the number of qubits needed for a useful quantum computer, one that could compete with your laptop in solving certain kinds of interesting problems, is between 1,000 and 100,000. So the number of continuous parameters describing the state of such a useful quantum computer at any given moment must be at least 21,000, which is to say about 10300. That's a very big number indeed. How big? It is much, much greater than the number of subatomic particles in the observable universe.

To repeat: A useful quantum computer needs to process a set of continuous parameters that is larger than the number of subatomic particles in the observable universe.

At this point in a description of a possible future technology, a hardheaded engineer loses interest. But let's continue. In any real-world computer, you have to consider the effects of errors. In a conventional computer, those arise when one or more transistors are switched off when they are supposed to be switched on, or vice versa. This unwanted occurrence can be dealt with using relatively simple error-correction methods, which make use of some level of redundancy built into the hardware.

In contrast, it's absolutely unimaginable how to keep errors under control for the 10300 continuous parameters that must be processed by a useful quantum computer. Yet quantum-computing theorists have succeeded in convincing the general public that this is feasible. Indeed, they claim that something called the threshold theorem proves it can be done. They point out that once the error per qubit per quantum gate is below a certain value, indefinitely long quantum computation becomes possible, at a cost of substantially increasing the number of qubits needed. With those extra qubits, they argue, you can handle errors by forming logical qubits using multiple physical qubits.

How many physical qubits would be required for each logical qubit? No one really knows, but estimates typically range from about 1,000 to 100,000. So the upshot is that a useful quantum computer now needs a million or more qubits. And the number of continuous parameters defining the state of this hypothetical quantum-computing machinewhich was already more than astronomical with 1,000 qubitsnow becomes even more ludicrous.

Even without considering these impossibly large numbers, it's sobering that no one has yet figured out how to combine many physical qubits into a smaller number of logical qubits that can compute something useful. And it's not like this hasn't long been a key goal.

In the early 2000s, at the request of the Advanced Research and Development Activity (a funding agency of the U.S. intelligence community that is now part of Intelligence Advanced Research Projects Activity), a team of distinguished experts in quantum information established a road map for quantum computing. It had a goal for 2012 that requires on the order of 50 physical qubits" and exercises multiple logical qubits through the full range of operations required for fault-tolerant [quantum computation] in order to perform a simple instance of a relevant quantum algorithm." It's now the end of 2018, and that ability has still not been demonstrated.

Illustration: Christian Gralingen

The huge amount of scholarly literature that's been generated about quantum-computing is notably light on experimental studies describing actual hardware. The relatively few experiments that have been reported were extremely difficult to conduct, though, and must command respect and admiration.

The goal of such proof-of-principle experiments is to show the possibility of carrying out basic quantum operations and to demonstrate some elements of the quantum algorithms that have been devised. The number of qubits used for them is below 10, usually from 3 to 5. Apparently, going from 5 qubits to 50 (the goal set by the ARDA Experts Panel for the year 2012) presents experimental difficulties that are hard to overcome. Most probably they are related to the simple fact that 25 = 32, while 250 = 1,125,899,906,842,624.

By contrast, the theory of quantum computing does not appear to meet any substantial difficulties in dealing with millions of qubits. In studies of error rates, for example, various noise models are being considered. It has been proved (under certain assumptions) that errors generated by local" noise can be corrected by carefully designed and very ingenious methods, involving, among other tricks, massive parallelism, with many thousands of gates applied simultaneously to different pairs of qubits and many thousands of measurements done simultaneously, too.

A decade and a half ago, ARDA's Experts Panel noted that it has been established, under certain assumptions, that if a threshold precision per gate operation could be achieved, quantum error correction would allow a quantum computer to compute indefinitely." Here, the key words are under certain assumptions." That panel of distinguished experts did not, however, address the question of whether these assumptions could ever be satisfied.

I argue that they can't. In the physical world, continuous quantities (be they voltages or the parameters defining quantum-mechanical wave functions) can be neither measured nor manipulated exactly. That is, no continuously variable quantity can be made to have an exact value, including zero. To a mathematician, this might sound absurd, but this is the unquestionable reality of the world we live in, as any engineer knows.

Sure, discrete quantities, like the number of students in a classroom or the number of transistors in the on" state, can be known exactly. Not so for quantities that vary continuously. And this fact accounts for the great difference between a conventional digital computer and the hypothetical quantum computer.

Indeed, all of the assumptions that theorists make about the preparation of qubits into a given state, the operation of the quantum gates, the reliability of the measurements, and so forth, cannot be fulfilled exactly. They can only be approached with some limited precision. So, the real question is: What precision is required? With what exactitude must, say, the square root of 2 (an irrational number that enters into many of the relevant quantum operations) be experimentally realized? Should it be approximated as 1.41 or as 1.41421356237? Or is even more precision needed? There are no clear answers to these crucial questions.

While various strategies for building quantum computers are now being explored, an approach that many people consider the most promising, initially undertaken by the Canadian company D-Wave Systems and now being pursued by IBM, Google, Microsoft, and others, is based on using quantum systems of interconnected Josephson junctions cooled to very low temperatures (down to about 10 millikelvins).

The ultimate goal is to create a universal quantum computer, one that can beat conventional computers in factoring large numbers using Shor's algorithm, performing database searches by a similarly famous quantum-computing algorithm that Lov Grover developed at Bell Laboratories in 1996, and other specialized applications that are suitable for quantum computers.

On the hardware front, advanced research is under way, with a 49-qubit chip (Intel), a 50-qubit chip (IBM), and a 72-qubit chip (Google) having recently been fabricated and studied. The eventual outcome of this activity is not entirely clear, especially because these companies have not revealed the details of their work.

While I believe that such experimental research is beneficial and may lead to a better understanding of complicated quantum systems, I'm skeptical that these efforts will ever result in a practical quantum computer. Such a computer would have to be able to manipulateon a microscopic level and with enormous precisiona physical system characterized by an unimaginably huge set of parameters, each of which can take on a continuous range of values. Could we ever learn to control the more than 10300 continuously variable parameters defining the quantum state of such a system?

My answer is simple. No, never.

I believe that, appearances to the contrary, the quantum computing fervor is nearing its end. That's because a few decades is the maximum lifetime of any big bubble in technology or science. After a certain period, too many unfulfilled promises have been made, and anyone who has been following the topic starts to get annoyed by further announcements of impending breakthroughs. What's more, by that time all the tenured faculty positions in the field are already occupied. The proponents have grown older and less zealous, while the younger generation seeks something completely new and more likely to succeed.

All these problems, as well as a few others I've not mentioned here, raise serious doubts about the future of quantum computing. There is a tremendous gap between the rudimentary but very hard experiments that have been carried out with a few qubits and the extremely developed quantum-computing theory, which relies on manipulating thousands to millions of qubits to calculate anything useful. That gap is not likely to be closed anytime soon.

To my mind, quantum-computing researchers should still heed an admonition that IBM physicist Rolf Landauer made decades ago when the field heated up for the first time. He urged proponents of quantum computing to include in their publications a disclaimer along these lines: This scheme, like all other schemes for quantum computation, relies on speculative technology, does not in its current form take into account all possible sources of noise, unreliability and manufacturing error, and probably will not work."

Editor's note: A sentence in this article originally stated that concerns over required precision were never even discussed." This sentence was changed on 30 November 2018 after some readers pointed out to the author instances in the literature that had considered these issues. The amended sentence now reads: There are no clear answers to these crucial questions."

Mikhail Dyakonov does research in theoretical physics at Charles Coulomb Laboratory at the University of Montpellier, in France. His name is attached to various physical phenomena, perhaps most famously Dyakonov surface waves.

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The Case Against Quantum Computing - IEEE Spectrum

COLLEGE PARK, Md.--(BUSINESS WIRE)--Researchers from The University of Maryland and IonQ, Inc. (IonQ) (NYSE: IONQ), a leader in trapped-ion quantum computing, on Monday published results in the journal Nature that show a significant breakthrough in error correction technology for quantum computers. In collaboration with scientists from Duke University and the Georgia Institute of Technology, this work demonstrates for the first time how quantum computers can overcome quantum computing errors, a key technical obstacle to large-scale use cases like financial market prediction or drug discovery.

Quantum computers suffer from errors when qubits encounter environmental interference. Quantum error correction works by combining multiple qubits together to form a logical qubit that more securely stores quantum information. But storing information by itself is not enough; quantum algorithms also need to access and manipulate the information. To interact with information in a logical qubit without creating more errors, the logical qubit needs to be fault-tolerant.

The study, completed at the University of Maryland, peer-reviewed, and published in the journal Nature, demonstrates how trapped ion systems like IonQs can soon deploy fault-tolerant logical qubits to overcome the problem of error correction at scale. By successfully creating the first fault-tolerant logical qubit a qubit that is resilient to a failure in any one component the team has laid the foundation for quantum computers that are both reliable and large enough for practical uses such as risk modeling or shipping route optimization. The team demonstrated that this could be achieved with minimal overhead, requiring only nine physical qubits to encode one logical qubit. This will allow IonQ to apply error correction only when needed, in the amount needed, while minimizing qubit cost.

This is about significantly reducing the overhead in computational power that is typically required for error correction in quantum computers," said Peter Chapman, President and CEO of IonQ. "If a computer spends all its time and power correcting errors, that's not a useful computer. What this paper shows is how the trapped ion approach used in IonQ systems can leapfrog others to fault tolerance by taking small, unreliable parts and turning them into a very reliable device. Competitors are likely to need orders of magnitude more qubits to achieve similar error correction results.

Behind todays study are recently graduated UMD PhD students and current IonQ quantum engineers, Laird Egan and Daiwei Zhu, IonQ cofounder Chris Monroe as well as IonQ technical advisor and Duke Professor Ken Brown. Coauthors of the paper include: UMD and Joint Quantum Institute (JQI) research scientist Marko Cetina; postdoctoral researcher Crystal Noel; graduate students Andrew Risinger and Debopriyo Biswas; Duke University graduate student Dripto M. Debroy and postdoctoral researcher Michael Newman; and Georgia Institute of Technology graduate student Muyuan Li.

The news follows on the heels of other significant technological developments from IonQ. The company recently demonstrated the industrys first Reconfigurable Multicore Quantum Architecture (RMQA) technology, which can dynamically configure 4 chains of 16 ions into quantum computing cores. The company also recently debuted patent-pending evaporated glass traps: technology that lays the foundation for continual improvements to IonQs hardware and supports a significant increase in the number of ions that can be trapped in IonQs quantum computers. Furthermore, it recently became the first quantum computer company whose systems are available for use via all major cloud providers. Last week, IonQ also became the first publicly-traded, pure-play quantum computing company.

About IonQ

IonQ, Inc. is a leader in quantum computing, with a proven track record of innovation and deployment. IonQs next-generation quantum computer is the worlds most powerful trapped-ion quantum computer, and IonQ has defined what it believes is the best path forward to scale. IonQ is the only company with its quantum systems available through the cloud on Amazon Braket, Microsoft Azure, and Google Cloud, as well as through direct API access. IonQ was founded in 2015 by Christopher Monroe and Jungsang Kim based on 25 years of pioneering research. To learn more, visit http://www.ionq.com.

About the University of Maryland

The University of Maryland, College Park is the state's flagship university and one of the nation's preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 40,000 students,10,000 faculty and staff, and 297 academic programs. As one of the nations top producers of Fulbright scholars, its faculty includes two Nobel laureates, three Pulitzer Prize winners and 58 members of the national academies. The institution has a $2.2 billion operating budget and secures more than $1 billion annually in research funding together with the University of Maryland, Baltimore. For more information about the University of Maryland, College Park, visit http://www.umd.edu.

Forward-Looking Statements

This press release contains certain forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Some of the forward-looking statements can be identified by the use of forward-looking words. Statements that are not historical in nature, including the words anticipate, expect, suggests, plan, believe, intend, estimates, targets, projects, should, could, would, may, will, forecast and other similar expressions are intended to identify forward-looking statements. These statements include those related to the Companys ability to further develop and advance its quantum computers and achieve scale; and the ability of competitors to achieve similar error correction results. Forward-looking statements are predictions, projections and other statements about future events that are based on current expectations and assumptions and, as a result, are subject to risks and uncertainties. Many factors could cause actual future events to differ materially from the forward-looking statements in this press release, including but not limited to: market adoption of quantum computing solutions and the Companys products, services and solutions; the ability of the Company to protect its intellectual property; changes in the competitive industries in which the Company operates; changes in laws and regulations affecting the Companys business; the Companys ability to implement its business plans, forecasts and other expectations, and identify and realize additional partnerships and opportunities; and the risk of downturns in the market and the technology industry including, but not limited to, as a result of the COVID-19 pandemic. The foregoing list of factors is not exhaustive. You should carefully consider the foregoing factors and the other risks and uncertainties described in the Risk Factors section of the registration statement on Form S-4 and other documents filed by the Company from time to time with the Securities and Exchange Commission. These filings identify and address other important risks and uncertainties that could cause actual events and results to differ materially from those contained in the forward-looking statements. Forward-looking statements speak only as of the date they are made. Readers are cautioned not to put undue reliance on forward-looking statements, and the Company assumes no obligation and do not intend to update or revise these forward-looking statements, whether as a result of new information, future events, or otherwise. The Company does not give any assurance that it will achieve its expectations.

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IonQ and University of Maryland Researchers Demonstrate Fault-Tolerant Error Correction, Critical for Unlocking the Full Potential of Quantum...