Tag: Quantum Computing

Quantum Computing in Banking and Finance – Threat or Opportunity?

What do companies such as J.P. Morgan, Wells Fargo, Barclays, Mitsubishi Financial Group, Citigroup, Goldman Sachs, or Caixa Bank have in common (besides being banking and financial giants)? They have all started to invest in and experiment with quantum computing applications.

Even though it is an emerging technology that still needs to mature in many ways to fulfill its wide range of promises, quantum computing has already started to make its way into various industries. The business world now faces steady pressure to familiarize itself with the technology, assess its potential, find specific use cases, and decide upon a potential long-term strategy.

Quantum computers are an entirely new type of hardware operating on quantum physics principles. While traditional computers use bits and a binary system of representing the information (either zero or one), quantum devices store the information in qubits, which can find themselves in a particular state, superposition (both zero and one at the same time). This allows them to process a vast amount of information significantly faster than classical devices. However, quantum hardware technology still needs to develop; therefore, most of the advantages that quantum computers offer compared to conventional computers are almost entirely theoretical.

Companies in the banking and financial sector are already experimenting with this technology to either harness its potential or take precautions with regard to its implications.

Quantum computing as a threat

Banks, hedge funds, asset managers, and all types of financial institutions deal with very sensitive customer data as well as information regarding transactions and contracts. Moreover, regulators require this data to be stored for periods ranging from several years to several decades. Therefore, it is paramount that it should remain secure and private. Some of the encryption algorithms used today rely on complex mathematical problems that classical computers cannot solve.

In a keynote presentation at the Inside Quantum Technology 2021 conference, Dan Garrison, who guided the creation of Accenture’s Quantum Computing Program, mentioned that if all classic computers would work together to break an encryption key (e.g., the one protecting a bank account), this would take approximatively 14 billion years. However, it has been theoretically proven that a quantum computer would be able to break some types of encryption in a matter of minutes or seconds, and several algorithms that can do that have already been developed.

Quantum hardware hasn’t yet reached the necessary level of development to run such algorithms. Nevertheless, as soon as large-scale, fault-tolerant universal quantum computers become available, there is a risk that all the data and private information concerning people, businesses, and transactions may be exposed. Some scientists expect this to happen in the next decade. Based on the principle “harvest now, decrypt later,” it is believed that nefarious actors are now hoarding encrypted data, with a view to accessing it as soon as more powerful quantum devices become available.

Therefore, by starting to use quantum-resistant algorithms already at this stage, the data owners could protect their information in the future, too.


“In the Finance sector, which deals with sensitive and private information, our greatest concern is what we call post-quantum cryptography (PQC). This refers to the landscape of privacy, cryptography, and encryption after the day when quantum computers become capable of breaking many of today’s encryptions. Post Quantum Cryptography should be something that is on everybody’s mind.” Peter Bordow, Principal Systems Architect for Advanced Technologies at Wells Fargo.


Quantum computing as an opportunity

Optimal arbitrage, credit scoring, derivative pricing – all these financial procedures involve many mathematical calculations and become even more complicated and resource-intensive as the number of variables increases. At some point, people have to settle for less-than-optimal solutions, because the complexity of the problem surpasses the capabilities of current technology and methods.

These so-called intractable problems (that can’t be solved by a traditional computer in a reasonable amount of time) represent the best use-cases for quantum technology.

One of the most acclaimed applications of quantum computing in the financial sector are the accurate simulation of markets and the ability to predict how a change in a commodity price will influence the cost of other assets.

According to experts in the field, quantum computers would be to perform so-called Monte Carlo simulations to forecast future markets, predict the price of options, or assess risk and uncertainty in financial models.

By optimizing machine learning and employing algorithms capable of recognizing patterns in large amounts of data, quantum computers could perform these highly complex forecasts and predictions.

Trading and portfolio optimization are other areas where quantum computing could significantly help. Having to consider the market volatility, customer preferences, regulations, and other constraints, traders are currently limited by computational limitations and transaction costs in simulating a large number of scenarios and improving portfolio diversification. Scientists have already proved that quantum technology can deal with the complexity of these problems.


Currently, Dharma Capital and Toshiba have joined forces in exploring the potential of quantum computers in assessing the effectiveness of high-frequency trading strategies for listed stocks in Japanese markets.


In a panel discussion during the Inside Quantum Technology 2021 conference, Steve Flinter, Vice President within Mastercard’s Artificial Intelligence & Machine Learning Department, declared that Mastercard had already started two years previously to explore use cases for quantum computers. Even though retail banking and payments are not typical use cases for these devices, Flinter believes that besides optimization problems, quantum computers could be successfully employed to make sense of petabytes of data.

Marcin Detyniecky, Group Chief Data Scientist and Head of AI Research and Thought Leadership at Axa Insurance, also points out that in the financial industry, quantum computers could have a positive impact in areas such as foreign exchange optimization, asset allocation, large-scale portfolio optimization, disaster simulations, and risk modeling.

Commercial quantum applications for the financial industry

Of the dozens of quantum software start-ups around the globe, Multiverse Computing and Chicago Quantum have already developed specific quantum solutions for the financial sector and announced encouraging results in the area of portfolio optimization.



Multiverse Computing’s most mature product, an investment optimization tool, is capable of improving asset allocation and management, generating twice the ROI on average while the risk and volatility remain constant. Besides that, the company develops quantum-inspired solutions to predict financial crashes, determine anomalies in big unlabeled datasets, and identify tax fraud.

Chicago Quantum’s proprietary algorithm identifies efficient stock portfolios and, according to the company, “is currently beating the S&P 500 and the NASDAQ Composite 100 indices”.

In terms of quantum security for financial institutions, there are already several companies on the market offering quantum encryption devices and solutions. QuintessenceLabs offers data-protection solutions and encryption keys based on quantum technology, designed to withstand any malicious attacks both from classical and quantum computers. ID Quantique is also commercializing a quantum random number generator, along with quantum-safe network encryption and quantum key distribution solutions. Similar services are provided by Cambridge QC, evolutionQ, IBM, Infineon, ISARA, and Microsoft, to name but a few.

“Wait and watch” or “go ahead”

The future development of quantum solutions within the financial and banking industry is not without challenges. Finding out which problems are suitable to be tackled by quantum computers and which not, increasing the interface accessibility and the availability of software, extending the interest in this technology beyond an elite group of mathematicians and physicians – these are only a few of the challenges that this field will have to deal with in the future.

However, experts have warned that adopting quantum-based solutions is a long and complex process that depends not only on the company’s capacity to define problems, migrate data, and adjust the infrastructure but also on its ability to include suppliers and clients in this process as well.


“This is a long game. It is not a light switch that you flip, and suddenly you’re all done in a few months, and you’ve mitigated all your risk exposure.” Peter Bordow, Principal Systems Architect for Advanced Technologies at Wells Fargo


Nonetheless, quantum computing technology is not fully developed yet, and most of its applications and promised benefits are still conceptual. Therefore, companies in the financial and banking industry are faced with two alternatives: To wait and watch, or to go ahead. The first option implies ignoring emerging trends and reacting only when the threats or the opportunities have been identified. The second one relies on a more proactive approach, where companies already start to familiarize themselves with the quantum technology, identify use cases, and start testing the integration of quantum security solutions. This option might prove more valuable in the long run and help them mitigate future risks.


Find out more about the expected breakthroughs in quantum computing. Read our report, Supertrends in Quantum Computing, for a complete overview of quantum technology, as well as key players and investors in this field.

© 2021 Supertrends

References

Egger, Daniel D, Gambella Claudio, Marecek Jakub, McFaddin Scott, Mevissen Martin, Raymon Rudy, Simonetto Andrea, Woerner Stefan, and Yndurain Elena. 2020. “Quantum Computing for Finance: State of the Art and Future Prospects.” IEEE Transactions on Quantum Engineering, vol. 1 (IEE Transactions ) 1-24.

Wells Fargo. 2020. Post-Quantum Cryptography (PQC) and the Quantum Threat. Position Report, San Francisco: Wells Fargo.

3D model of material 3D model of material 3D model of material 3D model of material

Towards the First Demonstration of Quantum Advantage in Material Discovery

New materials can bring tremendous benefits across all industries, from agriculture and construction to telecommunication, aerospace, medicine, the food industry, and the energy sector. However, most of the methods currently used for material discovery are based on trial-and-error procedures that require a significant amount of resources and take plenty of time to develop and implement. A hybrid approach using both classical and quantum devices along with machine learning and artificial intelligence tools – has the potential to bring material discovery to a new level of efficiency and speed.

The entire quantum computing industry is racing to achieve quantum advantage by proving that quantum computers can tackle real-life problems that otherwise cannot be efficiently solved by classic devices. Quantum annealers are a special type of quantum computers, mostly designed to address optimization problems. Applications are currently under development in several areas such as traffic flow optimization, manufacturing and logistic processes, performance, finance and trading algorithms.

In our interview with Dr. Michael Helander, President & CEO of OTI Lumionics, Dr. Helander explains how his team is preparing to demonstrate quantum advantage in materials discovery for the first time. The company uses high-performance computing simulations and machine learning algorithms to develop production-ready materials which are used in the manufacturing process of OLED displays in consumer electronics.

The screening of potential candidates for new materials is done using a combination of classical devices and quantum computing, thus eliminating the need for a wet-lab and the labor-intensive work of synthesizing and testing thousands of variations.


“We are somehow limited by what we can do with supercomputers today. It takes hours or even days to get the result of just one simulation. In the last six months, we have been able to demonstrate that we can start running commercially relevant-sized problems on real quantum hardware and get meaningful results back that outperform what classical hardware is capable of.”


The use of quantum computers significantly speeds up the process, scaling it up from thousands of simulations per week to tenths or hundreds of thousands. Problems are split up in two parts – one involving basic optimization (conducted on classical devices) and a second part – based on a discrete continuous algorithm (Genin, Ryabinkin, and Izmaylov 2019), which is solved on a quantum annealer[1] .

Building up on a strong collaboration with quantum computing providers, OTI Lumionics managed to perform the largest quantum chemistry calculation that was ever done on a quantum annealer. Dr. Scott Genin, Head of Materials Discovery and member of the research team mentioned that their findings will open up new perspectives for the use of quantum annealers and their methodology will allow for systematically improvable quantum chemistry calculations.

More funds are needed to reach a significant breakthrough in quantum computing

However, despite the huge potential of this field, one of the major concerns of scientists and businesses involved in this sector is a potential “quantum winter”; a period marked by a sector decrease in public interest and funding. In turn, this could significantly slow down the advancements and prevent the quantum industry to reach its potential.

Even if the quantum industry is currently flourishing and private and public funds are poured regularly into quantum research projects, Dr. Helander is convinced that by increasing the amount of funds, major breakthroughs would be possible much sooner.


“Think about Twitter. Only this company benefited from investments of over $1.5 billion. Imagine the speed and magnitude of advancements that could take place if quantum computing companies would benefit from similar investments.”


In the last decade, funds allocated by the Canadian government for research and development in the field of quantum computing amounted to approximately $1 billion [2]. Even though these funds were supplemented by private investments, they are still not enough to cover the level of research needed to propel quantum technologies to the next level.

As a founding member of Quantum Industry Canada (a consortium of private companies aiming to bring quantum technologies from the research lab into the industry), OTI Lumionics continues its quest to further develop quantum industrial applications and prove that quantum technologies can significantly increase business performance.


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© 2020 Supertrends

References

[1]Genin, Scott N., Ilya G. Ryabinkin, and Artur F. Izmaylov. 2019. “Quantum Chemistry on Quantum Annealers.” ArXiv:1901.04715 [Physics, Physics:Quant-Ph], January. http://arxiv.org/abs/1901.04715.

[2]Sussman, Ben, Paul Corkum, Alexandre Blais, David Cory, and Andrea Damascelli. 2019. “Quantum Canada.” Quantum Science and Technology 4 (2). https://doi.org/10.1088/2058-9565/ab029d.

Flying Qubits and Quantum Transistors – One More Piece in the Quantum Computing Puzzle

Developing components and systems for quantum information processing is a major task with a significant impact on the future of quantum computing. We are at a point where avid research is taking place in multiple directions; every little progress has the potential to shape the future of this industry. Within CEA Grenoble, Dr. Eleni Chatzikyriakou is working on simulating the operation of transistors, thus improving their functionality and performance. 

Along with efforts focused on building qubits and increasing their coherence time (the time spent by qubits in superposition), scientists all over the world are interested in the possibility of connecting qubits into complex circuits,  connecting multiple quantum devices, or developing hybrid devices, where both quantum and classical effects are harnessed simultaneously.

PHELIQS (Laboratoire PHotonique ELectronique et Ingénierie QuantiqueS) is a program developed within CEA Grenoble, aiming to find and test new solutions for creating devices that process quantum information. As a research fellow with a Ph.D. in Electronics and Computer Science and a strong interest in the quantum field, Dr. Eleni Chatzikyriakou contributes to this program by simulating the physical processes that take place in a quantum computer in order to find optimum designs that will improve transistor functionality.

In classical devices, transistors take care of the distribution of electric signals inside the machine. Similarly, a quantum transistor is meant to manipulate and transfer quantum information. However, due to the particularities of this technology, transistors have to function according to the principles of quantum physics as well. Even though some progress has been made, this technology is still in its infancy.

A way to transfer information between several quantum devices would be by using the so-called “flying (delocalized) qubits”. In this case, the quantum architecture would use stationary (localized) qubits to store data and perform computations. The information stored this way would then be transferred to a flying qubit, which will transport it to the next device and reconvert it into a stationary qubit.


“We are looking into technologies that incorporate various physical phenomena related to electrons, such as their spin or valley, or even delocalized electrons that take up more space but could be more robust than localized ones.”


Moreover, scientists within PHELIQS are also examining the possibility of performing logical operations on the qubits while they are being transmitted, making this channel more than just a means of data transport.

This process comes with multiple challenges, some of them relate to the accuracy of the transfer between a stationary and flying qubit, the flying qubit’s ability to preserve its coherence, and the distance it can cover. Like stationary qubits, scientists are testing different technologies to build flying qubits. One of the main questions is whether stationary and flying qubits could interact if they are built using various technologies, or if they must have a similar physical implementation.

Developing transistors and devices is a long and strenuous process, backed up by a lot of work on the theoretical level. Currently, most of the tests are carried out on classical computers, where various models are developed, evaluated, refined, and only then, applied in a laboratory setting.

Big players in the field of quantum computing have recently announced that they were able to perform operations faster than classical computers. However, this has also been questioned, as the decoherence of the qubits does not allow their number to increase beyond a certain threshold. Therefore, in some cases, classical computers are still faster than quantum devices. However, Dr. Chatzikyriakou remains optimistic that flying qubit technology can contribute to the robustness of the quantum devices.


When will we reach the next milestone in Quantum Technology?

At Supertrends, we crowdsource predictions about the future across worldwide industries – directly from the experts who are creating it. Visit the Supertrends App and search for ‘quantum computing’ to find out when various milestones for quantum technology are predicted to happen. Not an App user yet? Visit the Supertrends Pro – page to learn about your benefits and request a trial – for free!
© 2020 Supertrends

References

D. C. Glattli, J. Nath, I. Taktak, P. Roulleau, C. Bauerle,and X Waintal, Design of a single-shot electron detector withsub-electron sensitivity for electron flying qubit operation, arXiv:2002.03947

G. Fève, P. Degiovanni, and Th Jolicoeur, “Quantum Detection of Electronic Flying Qubits,” Physical Review B 77, no. 3 (January 8, 2008): 035308, https://doi.org/10.1103/PhysRevB.77.035308.

A Paradigm Shift. The Role of Quantum Mechanics in Arbitration, Politics, and Defense

For centuries, science has been based on Newtonian laws and the principles of classical physics. In the last decades, this ontology started to be questioned, leading to the rise of quantum mechanics. From theoretical simulations and mathematical experiments, these quantum principles soon extended to computer science. They are working their way into different industries, from manufacturing and chemistry to law, politics, and defense.

Classical mechanics picture the world as a collection of particles that find themselves under the influence of various electromagnetic forces. Repetitive measurements of a particle return similar results, and macroscopic phenomena are explained based on the properties of the microscopic level. Because of its simplicity and apparent consistency, this paradigm has been reinforced and has prevailed through time [1]. However, technological advancements have allowed scientists to observe and verify various phenomena that behave differently, giving rise to a vast array of experiments and applications [2].


“We currently live in a world in which the old Newtonian principles (cause-effect relationships) are no longer valid. The science stopped advancing, and the only way the society can move forward and progress is by implementing metaphysical postulates [3].”


A dedicated supporter of this paradigm shift, Amir Vahid founded Eonum, a company based in California that employs quantum principles and harnesses the power of quantum computers to develop solutions for risk management, arbitration, and outcome prediction.

Working on the quantum devices made available by IBM, Amazon Braket, or Stanford, Vahid’s model relies on the analysis of human emotion and considers live data instead of other companies in the field that rely on static information mathematical models to make predictions. According to Vahid, this has the potential to save up to 60% of the client’s litigation cost and predict court outcomes with a 90% accuracy.


“Eonum has a distinctive ability to quantify complex human emotion using quantum field theory to enable high impact decision making.”


Any type of conflict, either between companies, political opponents, or world-powers, involves a high level of uncertainty, emotional volatility, power imbalances, and mysterious information. Eonum’s quantum model aims to make sense of this data, providing their clients with a more realistic assessment of their chances and supporting them in the processes of risk assessment, litigation, or arbitration.

Eonum’s approach does not limit itself to the usage of quantum computers and AI to make sense of data and perform complex computations. The company also employs quantum-based strategies (e.g., social laser [4]) to support their clients to reach their goals. 

“An average lawsuit in the healthcare industry costs around 3 million USD. This is a costly and time-consuming process. Our strategy is to help our clients move towards conflict resolution before reaching court trials by laying out strategies based on quantum principles and computations.”

One of the significant advantages of this model resides in its flexibility. On one hand, the model develops continuously, which allows the prediction to change in real-time, based on the events that take place at that moment. On the other hand, it is scalable and transferable to problems in other areas such as politics and diplomacy.

Quantum computing applications are still in their infancy. Besides the advancements expected on the technical side, a significant change in mentality and the way of thinking is also paramount. Only this way, both academia and industries will bring this field to the next level and prove the universal validity of the dissipative quantum field theory.


What does the future hold?

At Supertrends, we crowdsource predictions about the future across worldwide industries – directly from the experts who are creating it. Visit the Supertrends App and search for ‘quantum computing’ to find out when various quantum computing applications are predicted to make breakthroughs. Not an App user yet? Visit the Supertrends Pro – page to learn about your benefits and request a trial – for free!
© 2020 Supertrends

References

[1] Rodolfo Gambini and Jorge Pullin, “Event Ontology in Quantum Mechanics and the Problem of Emergence,” n.d., 10.

[2] E. A. Rauscher, J. J. Hurtak, and D. E. Hurtak, “The Ontological Basis of Quantum Theory, Nonlocality and Local Realism,” Journal of Physics: Conference Series 1251 (June 2019): 012042, https://doi.org/10.1088/1742-6596/1251/1/012042.

[3] Hans Christian Öttinger, A Philosophical Approach to Quantum Field Theory (Cambridge, United Kingdom: CAMBRIDGE UNIVERSITY PRESS, 2018).

[4] Andrei Khrennikov, “‘Social Laser’: Action Amplification by Stimulated Emission of Social Energy,” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2058 (January 13, 2016): 20150094, https://doi.org/10.1098/rsta.2015.0094.

Honeywell: the time to build a strategy leveraging quantum computing is now

With a quantum volume of 128, Honeywell is one of the major players in the field of quantum computing, aiming to bring this technology to its full potential and harness its advantage in solving problems that span multiple industries.

Along with rampant developments in the field of quantum technology, the need for benchmarking and congruent measurements across this field has become imperative. Simply measuring the number of qubits is not relevant for the performance and efficacy of a quantum computer, together with a protocol for measuring it on current devices[1].

Quantum volume – the current metric in the quantum computing industry

Based on this metric (which takes into consideration not only the number of qubits but also the connectivity between them and the error rates), Honeywell announced in June 2020 that it reached a quantum volume of 64 on a 6-qubit quantum device. Then, in August 2020, IBM announced a quantum volume of 64 on a 27-qubit system[2].

In an interview with Supertrends, Justin Ging, Chief Commercial Officer for Honeywell Quantum Solutions, mentioned that the main factors leading to this performance are the technology chosen to build their qubits (trapped ion), their industry-leading gate fidelities and their unique QCCD (quantum charge coupled device) system architecture. Based on this milestone (quantum volume of 64), Honeywell is targeting a 10x improvement in quantum volume year-over-year for the next five years. The first step in this direction has already been made, with Honeywell reaching a quantum volume of 128 in September 2020[3].

What does this mean in terms of industry applicability?

Honeywell envisions that quantum computing will have a far-reaching impact on multiple industries; ranging from classical optimization problems (e.g., the travelling salesman and knapsack problems) that are intractable at large scales, to more efficient training of large-scale machine learning models and high-fidelity simulations of complex chemical reactions and compounds.


“From aircraft networks to postal routes, quantum computing has the potential to change it all for the better.”


This way, companies that currently rely on heuristics and simplistic models can have access to better solutions for the problems they are facing.

Currently, Honeywell’s quantum computer can be accessed via a cloud computing service. The company set up an API that customers can use to plug directly into the system. They also partnered with Microsoft to offer their system through the Azure Quantum platform.

What will a world with quantum computers look like?

Honeywell declared that quantum computing should not be seen as a panacea or as a replacement for classical computers. The vision for the future is that both technologies will coexist in a hybrid computing environment, with upcoming computing architectures that will offer access to QPUs (quantum processing units).

So far, quantum devices haven’t yet reached the so-called “quantum advantage” (the capacity to solve problems that are impossible to be solved on a classical device). Companies, research centers and universities are still experimenting with different technologies and are testing multiple problems in order to find the means and the areas where quantum computers will make a significant difference. However, since working with quantum computers involves a new way of defining and analyzing problems, Ging mentions that it is important for companies to begin preparing now, in order to take advantage of the technology when it becomes available.


“The time to build a robust strategy leveraging quantum computing is now. Those companies that are currently interacting with and exploring the technology will be the ones disrupting their respective industries in the future.”


Supertrends: driven by expert insights

Our goal at Supertrends is to raise awareness about the significant scientific, technological, economic and social developments that will shape our future as we know it. Thus, we provide a platform for the voices of the groundbreaking experts, scientists, developers and entrepreneurs across a wide variety of industries. If you think you might be one of them, learn more about becoming a Supertrends expert here. If you’d like to continue reading, you can explore our growing list of article topics featuring Supertrends experts below:

© 2020 Supertrends

References

[1]Andrew W. Cross et al., “Validating Quantum Computers Using Randomized Model Circuits,” Physical Review A 100, no. 3 (September 20, 2019): 032328, https://doi.org/10.1103/PhysRevA.100.032328.

[2]“IBM Delivers Its Highest Quantum Volume to Date, Expanding the Computational Power of Its IBM Cloud-Accessible Quantum Computers,” IBM News Room, September 23, 2020, https://newsroom.ibm.com/2020-08-20-IBM-Delivers-Its-Highest-Quantum-Volume-to-Date-Expanding-the-Computational-Power-of-its-IBM-Cloud-Accessible-Quantum-Computers.

[3]“Achieving Quantum Volume 128 on the Honeywell Quantum Computer,” accessed October 1, 2020, https://www.honeywell.com/content/honeywell/us/en/newsroom/news/2020/09/achieving-quantum-volume-128-on-the-honeywell-quantum-computer.html.

The biggest obstacle to quantum computing is… noise?

We spoke to Jessica Pointing, a world-renowned quantum computing expert and Harvard graduate currently pursuing a Ph.D. in Quantum Computing from Stanford University. Among the interesting insight she shared with us, she explained how various types of noise can affect quantum computations and what can be done to eliminate or avoid the resulting errors.

In the quantum context, ‘noise’ is not an undesirable sound. It is interference that can be caused by internal and external factors. External factors usually include: magnetic fields, variation in temperature, impurities in the qubit material, stray atoms or vibrations. The internal noise could be determined by the interactions between the qubits themselves, because of their entanglement (specific relation between pairs of qubits) and the fact they need to interact in order to perform computations. For more information about entanglement, check out Jessica’s explanation at the 2019 GOTO Conference.

Jessica Pointing at one of the GOTO Conferences, explaining the notion of qubits and superposition.

The current stage of development of this technology is defined as NISQ (noisy intermediate scale quantum) and is considered to be a step towards the real, robust quantum computer of the future.

In the meantime, scientists are hard at work discovering ways to detect and cancel noise[1]. As the technology improves, fault tolerance or a specific threshold for noise where quantum computers are considered reliable and sufficiently accurate will increase, making quantum computers reliable enough to work for extended periods of time at full capacity.

Noise and “soft” workarounds

The longer the computer program runs, the more time there is for errors. Despite the error-prone nature of quantum computers, Google ran an experiment on a quantum computer demonstrating that it was able to perform a calculation faster than even the best supercomputers. Google claimed the calculation would take 10,000 years on a supercomputer, but only 200 seconds on their quantum computer[2]. Nevertheless, researchers are exploring applications of this experiment.

The ideal method to reach an error-free computation would be error correction. It has been proven theoretically, and the topic is being studied in various research centers.


“Error correction requires a redundancy of qubits (for every ‘functional’ qubit you would need several others to perform error corrections). Given the fact that the maximum number of qubits available in a quantum computer is currently 53, there is not much room left for both computations and error-correction. A proper and fully reliable quantum computer would require a very large number of qubits”


The technique currently employed in working with NISQs is error mitigation, a way to deal with quantum errors through post-processing with different types of algorithms. According to other scientists, a possible solution could also lie in the software used: “writing quantum software in such a way that errors do as little harm as possible… can work even if we have imperfect knowledge of the nature of the errors, as will certainly be the case in reality”[3] .

Error-free quantum computing, the next step

There is still a long way to go before a fully fault-tolerant quantum computer becomes reality. Up until now, hardware companies have been focusing on building the hardware and creating functional qubits. Now there is an opportunity to explore applying error correction to the quantum devices that have been built.

It is possible that other technologies for developing qubits will be discovered and these will be less prone to errors due to noise. Currently the most common technologies used to build qubits are superconducting circuits, trapped ions, photons, and diamonds.


Visit the Supertrends App and search for ‘quantum computing’ to read Jessica’s predictions of when future milestones in quantum technology may be attained. Not an App user yet? Visit the Supertrends Pro – page to learn about your benefits and request a trial – for free!
© 2020 Supertrends

References

[1]“Researchers Advance Noise Cancelling for Quantum Computers,” accessed September 17, 2020, https://phys.org/news/2019-09-advance-noise-cancelling-quantum.html.

[2]Frank Arute et al., “Quantum Supremacy Using a Programmable Superconducting Processor,” Nature 574, no. 7779 (October 2019): 505–10, https://doi.org/10.1038/s41586-019-1666-5.

[3]Suguru Endo, Simon C. Benjamin, and Ying Li, “Practical Quantum Error Mitigation for Near-Future Applications,” Physical Review X 8, no. 3 (July 26, 2018): 031027, https://doi.org/10.1103/PhysRevX.8.031027.

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Delivering value right now with quantum computing

Some refer to quantum computers as a big technological bubble in which people will soon lose interest, others believe that it might take decades to see some significant breakthrough in this field. For other companies and experts, quantum computing is already here. Tina Sebastian, CEO of Quacoon and a seasoned expert in both computer science and manufacturing, is convinced that quantum technology can already bring significant value to Industry 4.0 and supply chain management.

Where do all these different views come from? First of all, it depends on the technology and the quantum computing method employed. Some are closer to real-life applications; while others are in the early experimental phase. Secondly, it depends on the type of problem scientists attempt to tackle. A quantum computer might provide competitive value sooner in optimization problems, than in areas such as drug design or material science. Thirdly, it strongly depends on the people’s perspective. Theoretical and academic researchers tend to be more reserved, while business representatives are more eager to find use cases and practical applications for each technological advancement.

Different technologies, different applications

Currently, the main quantum computing methods are the universal quantum gate model and the quantum annealing. While gate-based models are expected to have applications in a large variety of areas (including breaking RSA cryptography), quantum annealers run adiabatic quantum algorithms and focus on a narrower niche; namely on problems which involve choosing the optimum answer among a large number of solutions. These so-called “optimization problems” have a high number of variables, with multiple interactions and constraints among them. As these variables and interactions scale exponentially, a classical computer cannot handle them anymore. Or, the time necessary to get a response would be too long for the solution to be considered useful.

Added value in the manufacturing industry

Quacoon aims to bring quantum annealers and their adiabatic algorithms into the manufacturing sector, with a focus on supply chain optimization and traceability. In combination with other technologies such as blockchain and artificial intelligence, quantum computing is considered a viable solution in making supply chains more reactive in real-time.


Think about how the first months of the COVID-19 pandemic were marked by a shortage of certain products. Even if we have educated experts to design the best supply chains possible, the current classical computers encounter problems when faced with unexpected situations. There is still a lack of flexibility and reactivity, which in turn leads to shortages and disruptions.”


Adjusting to sudden and unexpected changes in the environment currently requires human intervention, intensive pen-and-paper labor to recalculate schedules, minimize downtime, and re-establish the previous level of productivity. Sebastian is convinced that quantum technology can be invaluable in these types of situations by recalculating the major parameters in real-time and minimizing losses.

Beyond manufacturing

Despite being considered by some critics as simply glorified versions of classical computers, quantum annealers are a significant part of the quantum ecosystem. Besides companies such as D-Wave that build and provide access to hardware, some start-ups develop applications tailored to this technology and conduct pilot projects within different industries. For example, Volkswagen used a quantum annealer for the first time with a real-time workload to manage its fleet of buses. Meanwhile, Toyota used the technology for traffic signal optimization. Other possible applications are envisioned in the design of peptides, computational biology, optimization problems in healthcare or quantum-assisted training of deep neural networks.

However, as in any emergent field, there is much uncertainty as to which technology will bring the highest return on investment and will provide the much expected “quantum advantage” (solving a real-life problem that is not solvable on a classical computer). Therefore, most solution providers, including Quacoon, develop their algorithms to be compatible with multiple hardware platforms and to assure a scalable architecture that can be employed irrespective of the particularities of the problem.  


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Bringing molecular simulations a step further

What can we do with the near-term quantum devices that we currently have? What are the benefits that they bring, and what is their future potential? Is it possible for the actual NISQ (Noisy Intermediate-Scale Quantum) devices to further advance the fields of material and drug discovery through complex molecular simulations and modelling that are difficult to generate on a classical computer?

These are some of the main topics on quantum scientists’ research agenda and a strong point of interest for Sayonee Ray, a post-doctoral fellow at the Center for Quantum Information and Control in New Mexico. After finishing her Ph.D. in theoretical physics, she started working at the interface between quantum information, quantum optics, and many-body physics. In an attempt to deepen the understanding of quantum systems from a theoretical point of view, Ray develops simulations and models of quantum systems, comparing their performance to that of classical computers.

Molecular simulation allows researchers across various fields to understand complex processes and principles; interactions that take place at an atomic level that are not always accessible via experiments (e.g., how molecules bind to their receptors – very helpful in the drug development process, the protein folding process, etc.)

Despite note being very robust yet and being somewhat prone to errors, the current quantum devices can already model molecular configurations. After accurately simulating a molecule for the first time in 2016 [1], Google managed to simulate a chemical reaction in 2020 [2].

These operations can already be easily done on a classical computer. In fact, researchers currently use traditional devices to check the accuracy of quantum results. Applications on current quantum devices are still in their infancy, still trying to catch up with operations that are already possible on a traditional machine. However, due to their specific way of functioning, once they scale up, it is expected that quantum computers will surpass classical devices in certain industries and for specific problems.


“Quantum computers are not going to replace classical computers entirely. They will be used in certain industries, for specific tasks, such as determining the molecular structure of a very complicated drug, or testing the interaction between different molecules.” 


Ray sees quantum computers as having tremendous potential in a broad array of areas, from biochemistry, engineering and material science to finance, medicine and pharma. However, she considers the quantum simulation of complex chemical systems as one of the most promising applications of this technology.

Yet many milestones still need to be crossed before this application becomes a reality. Not only does the quality of qubits need to be enhanced and the errors and noise decreased, but also the quality and efficiency of algorithms and software need to be improved.


“It is for all of us a learning process. Everybody is trying at the same time, on different levels and in different areas, so something is definitely going to happen.” 


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© 2020 Supertrends

References

[1]O’Malley, P., Babbush, R., Kivlichan, I. et al., 2016. Scalable Quantum Simulation of Molecular Energies. Physical Review X, [online] 6(3). Available at: <https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.031007> [Accessed 16 September 2020]. 

[2]Rubin, N. and Babbush, R., 2020. Hartree-Fock on a superconducting qubit quantum computer. Science, [online] (6507), pp.1084-1089. Available at: <https://science.sciencemag.org/content/369/6507/1084> [Accessed 16 September 2020]. 

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Quantum computers are coming. What about quantum software?

With the rise of quantum hardware providers that make some of their devices available to the public through cloud services, the number of companies working to develop quantum software – tools, algorithms, programming languages and applications – for this innovative technology has increased substantially. So has the complexity of the field and the differences in perspectives and approaches.

Along with developing functional qubits and the hardware technology to support quantum computing, an entire plethora of software components needs to be developed as well. Denise Ruffner, Chief Business Officer at Cambridge Quantum Computing (CQC) and one of the pioneers in the field of quantum computing, is fully aware of the challenges involved.


“Current software won’t apply to quantum computers. If there is a problem that a quantum computer can solve, new software has to be written.”


Working with quantum devices requires a completely new way of thinking, different ways of conceptualizing problems and therefore, different solutions in terms of programming languages, compilers, test programs and optimization tools.

 The major providers of full stack quantum solutions already developed programming languages for their computers. Rigetti created Forest, an environment to write and run quantum programs, IBM developed QISKit (Quantum Information Software Kit), Microsoft provides the Quantum Development Kit, Google makes use of Cirq while Xanadu advances Strawberry Fields and Blackbird for their photon-based quantum computer, just to name a few. Besides the aforementioned, there are also multiple organizations and research centers collaborating with hardware providers and developing their own quantum software ecosystem and programming languages (e.g., Q-CTRL, Zapata Computing, etc.)

Since the software is highly dependent on the technology used to build quantum computers, and this technology is still under development, Ruffner mentions that “it is hard to predict which software will be on the lead.”


“I once had a customer who called me and said, ‘I have written the software on Rigetti’s Forest and now I want to run it on Qiskit. Can you send me the software that translates Rigetti’s Forest into Qiskit?’ I replied to him ‘There’s nothing like that. You have to re-write your software in Qiskit.’ It took them six months to do that.”


In order to address this problem, CQC developed a quantum development platform (t|ket⟩™), enabling clients and partners to use their software on different quantum devices and work across multiple platforms.

t|ket⟩™ allows companies to hedge their bets, test several quantum devices and choose the one that provides the best results for the type of problem they want to tackle. Besides the flexibility provided through translating existing software into the one supported by the device, CQC’s development platform also optimizes the algorithms, reducing their length and duration.

This proves to be especially useful when it comes to the noise and error problems inherent to the current NISQ (Noisy Intermediate-Scale Quantum) computers. In current quantum devices, the longer an algorithm runs, the higher its exposure to noise and errors. By reducing its runtime, t|ket⟩™ also allows for improved calculation results.

The field of quantum computing cannot simply build upon the competencies and knowledge derived from classical computing. Moreover, simply writing an algorithm hoping to implement it when the quantum computer comes along is also not feasible.

These algorithms have to go through several validation processes in which problems are reduced to a low complexity level, worked out in a quantum computer and then have the answer validated via a classical computer. The complexity of the problem is then increased, a quantum answer is obtained and it is tested again through a classical algorithm. At some point, the problem becomes so complex that a classical test is not possible anymore, but the trajectory built up to that moment can vouch for the validity of the results obtained via the quantum solution. 


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© 2020 Supertrends

Quantum computing – no black magic but definitely mind-bending

Forget anything you know about classical computers and the way they work. Open your mind and be prepared to see computational work from an entirely new perspective on a completely new level.

Back in 1900 people couldn’t imagine what a computer could be used for. Fast forward to 2019 and there are over 2 billion computers and the number is increasing. This is a stark contrast to Watson’s assumption in 1943 that “[…] there is a world market for maybe five computers”. The need for data processing is increasing exponentially and the calculations required are constantly increasing in complexity, therein the need for quantum computers.

According to our expert, Preben Thorø (Chairman of the GOTO Conference Program Committees and CTO at Trifork GmbH), the need for quantum computers, although limited now will become a mainstay in the near future. The need for faster and more efficient computers is a given, but…

What is quantum computing, and how is it different from classical computing?

Even if both quantum computers and classical computers are used to solve problems, the main differences reside in the technology involved, the magnitude of the problems, and the way data is manipulated. Based on quantum physics principles, quantum computers make use of superposition (the capacity of a quantum object to exist in multiple states simultaneously) and entanglement (the idea that two particles are in sync even when they are separated from each other).

Therefore, if a classical computer uses bits which can be either 0 or 1, a quantum computer uses Qbits. When these Qbits find themselves in superposition, they are at the same time both 0 and 1 (this is where philosophy and physics come together. Until you observe the Qbit, all you know is that there will be a certain possibility of measuring a 0 and a certain possibility to measure a 1, so until you do the measurement, it is floating around in superposition being both 0 and 1). This, together with the entanglement between Qbits and the probabilities associated with the superpositions, allows for a faster processing of extremely large quantities of data. Rather than the number of Qbits, the coherence time (the period in which the Qbit can remain in superposition) is one of the most important criteria when it comes to evaluating the performance of a quantum computer.

Another central aspect that differentiates between quantum computers and classical ones is the building technology. Because any interference or noise in the system will affect the superposition characteristics, quantum computers must – for the time being – run at temperatures close to absolute zero (below 100 mK, or -273.05°C) which is even lower than interstellar space.

Why do we even need quantum computers?

As days go by, world problems become more and more complex, and humanity will soon run out of traditional computational power to solve them (or not have enough time to see these problems solved). From optimization challenges to simulating and modelling molecular structures, quantum computers might work their way into the chemical industry (potential to develop new materials), fintech (portfolio optimization), logistics and auto industry (traffic optimization and battery improvement), pharma (drug discovery), and defense (cybersecurity).

Preben believes that within relatively few years to come quantum computers will be capable of breaking the AES-256 encryption standard (a key with a length of 256 bits which to be broken would require the processing of 1.1×1077 combinations), which is the current de-facto encryption used by most internet sites. According to the Supertrends app, the current consensus indicates that this might happen around 2031. This opens the door for the development of an entirely new sector in the field of cybersecurity and cryptography, companies, and governments needing to restructure their entire data security structure.

Competitive advantage

Powered by the industry’s key players (Google, IBM, Microsoft) and pushed forward by the private market (D-Wave, Honeywell, Rigetti and Xanadu), the quantum computing field is in continuous development, with over 150 start-ups covering various aspects such as hardware components, software, applications, quantum sensing, and security. Prestigious universities worldwide (Oxford, Harvard, MIT, as well as technological universities in Singapore, China, California, Australia, Germany, Austria and Switzerland) conduct research projects to explore the potential of quantum information technologies and the future possible applications.

In this respect, being “quantum ready” doesn’t only mean to have an encryption system that is unbreakable, but to understand the tremendous potential quantum computing holds. The first companies to harness its power will unquestionably gain a competitive advantage and differentiate themselves on the market.


This article only scratches the surface of the quantum computing field. In our “Supertrends in Quantum Computing” dynamic report, we take a deep dive into the current quantum computing technology ecosystem as well as the key players and investors involved. Furthermore, as Supertrends reports are dynamic, we will regularly update its information with major developments and promising new technologies within the field. Click here to learn more.

© 2020 Supertrends

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