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LONDON, Jan. 4, 2021 /PRNewswire/ -- The cover story of this 226 page issue features the impressive Dame Jayne-Anne Gadhia, formerly of Virgin Money, who founded Snoop in 2020. And her start-up leads us into a feature length piece of investigative journalism from Emily Cashen on open banking and fintech.

The use of physical cash has been decreasing for many years now and a global pandemic with enforced shutdowns hastened that trend. Laura French explores whether we are now ready to embrace a cashless world.

Elsewhere in the magazine, Alex Katsomitros explores the potential impact of a set of proposals from the OECD that would completely reform corporation tax, put together after continued concerns over inequality and the need for a post-pandemic economic recovery.

Meanwhile, with governments the whole world over providing loans and financial aid packages to levels never previously seen before, Selwyn Parker discusses what happens next as we potentially venture into a sea of debt.

Additionally, Richard Willsher looks at how the forex markets navigated a pandemic by seamlessly shifting operations to a WFH environment thanks to the rise of e-platforms and online tools.

Topics also covered in the winter edition of World Finance includecryptocurrencies, corporate art, shipbuilding, Zoom's breakthrough year, quantum computing and recession success stories.

To read about all of this and more, pick up the latest issue of World Finance magazine, available in print, on tablet and online now.

http://www.worldfinance.com

World News Media is a leading publisher of quality financial and business magazines. It benefits from a global distribution network that includes subscriber lists of prominent decision-makers around the world.

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World Finance offers in-depth and high-quality journalism on a huge variety of topics in its eagerly anticipated Winter 2021 issue, released today -...

Quantum computing has opened multiple doors of possibilities for quick and accurate computation for complex problems, something which traditional methods fail at doing. The pace of experimentation in quantum computing has very naturally increased in recent years. 2020 too saw its share of such breakthroughs, which lays the groundwork for future innovations. We list some of the significant quantum computing projects and experiments of 2020.

IT services company Atos devised Q-Score for measuring quantum performance. As per the company, this is the first universal quantum metric that applies to all programmable quantum processors. The company said that in comparison to qubits, the standard figure of merit for performance assessment, Q-Score provides explicit, reliable, objective, and comparable results when solving real-world optimisation problems.

The Q-Score is calculated against three parameters: application-driven, ease of use, and objectiveness and reliability.

Googles AI Quantum team performed the largest chemical simulation, to date, on a quantum computer. Explaining the experiment in a paper titled, Hartree-Fock on a superconducting qubit quantum computer, the team said it used variational quantum eigensolver (VQE) to simulate chemical mechanisms using quantum algorithms.

It was found that the calculations performed in this experiment were two times larger than the previous similar experiments and contained about ten times the number of quantum gate operations.

The University of Sydney developed an algorithm for characterising noise in large scale quantum computers. Noise is one of the major obstacles in building quantum computers. With this newly developed algorithm, they have tried to tame the noise by reducing interference and instability.

A new method was introduced to return an estimate of the effective noise with relative precision. The method could also detect all correlated errors, enabling the discovery of long-range two-qubit correlations in the 14 qubit device. In comparison, the previous methods would render infeasible for device size above 10 qubits.

The tool is highly scalable, and it has been tested successfully on the IBM Quantum Experience device. The team believes that with this, the efficiency of quantum computers in solving computing problems will be addressed.

Canadian quantum computing D-Wave Systems announced the general availability of its next-generation quantum computing platform. This platform offers new hardware, software, and tools for accelerating the delivery of quantum computing applications. The platform is now available in the Leap quantum cloud service and has additions such as Advantage quantum system with 5000 qubits and 15-way qubit connectivity.

It also has an expanded solver service that can perform calculations of up to one million variables. With these capabilities, the platform is expected to assist businesses that are running real-time quantum applications for the first time.

Physicists at MIT reported evidence of Majorana fermions on the surface of gold. Majorana fermions are particles that are theoretically their own antiparticle; it is the first time these have been observed on metal as common as gold. With this discovery, physicists believe that this could prove to be a breakthrough for stable and error-free qubits for quantum computing.

The future innovation in this direction would be based on the idea that combinations of Majorana fermions pairs can build qubit in such a way that if noise error affects one of them, the other would still remain unaffected, thereby preserving the integrity of the computations.

In December, Intel introduced Horse Ridge II. It is the second generation of its cryogenic control chip, considered a milestone towards developing scalable quantum computers. Based on its predecessor, Horse Ridge I, it supports a higher level of integration for the quantum systems control. It can read qubit states and control several gates simultaneously to entangle multiple qubits. One of its key features is the Qubit readout that provides the ability to read the current qubit state.

With this feature, Horse Ridge II allows for faster on-chip, low latency qubit state detection. Its multigate pulsing helps in controlling the potential of qubit gates. This ability allows for the scalability of quantum computers.

I am a journalist with a postgraduate degree in computer network engineering. When not reading or writing, one can find me doodling away to my hearts content.

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Major Quantum Computing Projects And Innovations Of 2020 - Analytics India Magazine

Mergingquantum computing with artificial intelligence (AI)has been on the priority list for researchers and scientists. Even though quantum computing is still in the early phases of development, there have been many innovations and breakthrough. However, it is still unclear on whether the world will change for good or bad when AI is totally influenced by quantum computing.

Quantum computingis similar to traditional computing. It relies on bits, which are 0s and 1s to encode information. The data keeps growing despite limiting it. Moores law has observed that the number of transistors on integrated circuits wills double every two years, making way for tech giants to run the race of making the smallest chips. This has also induced tech companies to compete for the first launch of a viable quantum computer that would be exponentially more powerful than todays computers. The futuristic computer will process all the data we generate and solve increasingly complex problems.

Remarkably, the use ofquantum algorithms in artificial intelligencetechniques will boost machines learning abilities. This will lead to improvements in an unprecedented way. The main goal of the merger is to achieve a so-calledquantum advantage, where complex algorithms can be calculated significantly faster than with the best classical computer. The expected change will be a breakthrough in AI. Experts and business leaders predict thatquantum computings processing powercould begin to improve AI systems within about five years. However, combining AI and quantum is considered scary from an angle. The late researcher and scientist Stephen Hawking has said that the development of full AI could spell the end of the human race. Once humans develop AI, it will take off on its own and redesign itself at an ever-increasing rate. Humans, who are limited by slow biological evolution couldnt compete and would supersede.

Can solve complex problems quickly

One of the major expectations that people have fromquantum computingis to have increased computational skill. It is predicted that quantum computers will be able to complete calculations within seconds that would take thousands of years to calculate. Google claims that the company has a quantum computer that is 100 million times faster than any existing computer. This futuristic and quick way of calculating will solve all the data problems in minutes if not seconds. The key to availing the transition is by converting all the existing data into quantum language.

Enhance warfighter capabilities

Even though the improvement of quantum computing is in the initial stage, it is expected to enhance warfighter capabilities significantly in the future. It is predicted that quantum computing is likely to impact ISR (intelligence, surveillance and reconnaissance), solving logistic problems more quickly. While we know the types of problems and general application space, optimisation problems will be some of the first where we will see advantages.

Applications in the banking sector

Malpractice and constant forgeries are common in the banking and financial sector. Fortunately, the combination of AI with quantum computing might help improve and combat fraud detection. Models trained using a quantum computer will be capable of detecting patterns that are hard to spot using conventional equipment. Meanwhile, the acceleration of algorithms will yield great advantages in terms of the volume of information that the machines handle for this purpose.

Help integrate data from different datasets

Quantum computers are anticipated to be experts in merging different datasets. Although this seems quite impossible without human intervention in the initial phase, computers will eventually learn to integrate data in the future. Henceforth, if there are different raw data sources with unique schema attached to them and a research team wants to compare them, a computer would have to understand the relationship between the schemas before the data could be compared.

All is not good though

In some way, AI and quantum computing worry people with an equal amount of expectations it gives. Quantum computing technology will be very futuristic, but we cant assure you that it is human-friendly. It could be far better than humans suppressing people in their jobs. Quantum computing also poses athreat to security. The latest Thales Data Threat report says that 72% of surveyed security experts worldwide believe quantum computing will have a negative impact on data security within the next five years.

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Quantum Computing Entwined with AI is Driving the Impossible to Possible - Analytics Insight

A famous story about the Beatles tells of the collaboration between Paul McCartney and John Lennon on the song Getting Better for their legendary Sgt. Pepper's Lonely Hearts Club Band album. After McCartney wrote the lines I've got to admit, it's getting better; a little better all the time, Lennon wryly added, It can't get no worse. This story could serve as an epigraph as the calendar turns from the year 2020, which could hardly have gotten much worse, to 2021, when we hope life will indeed get a little better all the time. Better from COVID-19 because of the vaccines, better from misinformation spread by outgoing president Donald Trump and his allies, and better, we can hope, when it comes to the production and distribution of scientific knowledge.

There's plenty of exciting science to be optimistic about in 2021 (see News on p. 6). At the end of 2020, the DeepMind group in the United Kingdom announced a major advance in long-standing challenges in protein folding, predicting three-dimensional (3D) structures of proteins from their amino acid sequence. The next year portends even more exciting advances in protein structure and design.

On the cosmic front, there are many efforts underway to bring samples from the Solar System back to this planet. The Hayabusa2 mission that traveled to the asteroid 162173 Ryugu retrieved what could be a treasure trove of material revealing details about the ancient delivery of water and organic molecules to Earth. Similarly, the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer) mission has collected samples from the asteroid Bennu that, when they arrive, could reveal important aspects of the formation of the Solar System. The new Mars rover Perseverance will land in February and, in addition to transmitting important data from the red planet, will begin the process of collecting samples that may eventually be studied in terrestrial laboratories.

In biology, the COVID-19 pandemic led to major advances in the development and application of messenger RNA (mRNA) vaccines. It is stunning that science not only came up with a vaccine to a new pathogen so quickly but also advanced a brand new vaccine technology, albeit one that was already in development for several years. The application of mRNA therapies to other problems in infectious diseases and throughout medicine will be exciting to follow.

Quantum computing remains an important area to watch. This year, Science published a paper that describes the application of a quantum computer to an important problem in theoretical chemistry. In the coming months, it's likely that there will be progress in addressing the problem of quantum error correction, pushing quantum computing a little closer to routine application.

Additive manufacturing and 3D printing continue to become more practical. In particular, the ability to apply these techniques to new types of materials will make it more likely that advanced manufacturing can benefit from the science behind these processes.

On the policy front, the continued development of the UK Research and Innovation (UKRI) organizationas described in a recent editorial by Ottoline Leyserwill be of keen interest as the Brexit process continues. Despite choppy politics, the scientific vision of UKRI is strong and could lead to advances in British science.

In the United States, although the Biden White House will certainly be friendlier to science, the science denial that fueled the Trump administration will linger in the American population and among some conservative politicians. The battles ahead are not to be underestimated. Continued denial of climate change and COVID-19 is sadly inevitable, and it will take everything U.S. science and the Biden administration can muster to stay strong. Still, as new leaders are named and confirmed in health and science policy, U.S. science should be able to at least catch its breath and feel optimistic about a new era.

Although 2020 will certainly go down as a year that couldn't get much worse, there is plenty to be proud of and reason to hope that things will be getting better. The virus was confronted. Epidemiologists and other scientists became household names. And the scientific community found a much stronger voice, one that will serve us all well in 2021 and beyond.

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A little better all the time in 2021 - Science Magazine

At a conference on quantum computing and finance on December 10, 2020, William Zeng, head of quantum research at Goldman Sachs, told the audience that quantum computing could have a revolutionary impact on the bank, and on finance more broadly. In a similar vein, Marco Pistoia of JP Morgan stated that new quantum machines will boost profits by speeding up asset pricing models and digging up better-performing portfolios. While there is little dispute that quantum computing has great potential to perform certain mathematical calculations much more quickly, whether it can revolutionize investing by so doing is an altogether different matter.

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Q3 2020 hedge fund letters, conferences and more

The hope is that the immense power of quantum computers will allow investment managers earn superior investment returns by uncovering patterns in prices and financial data that can be exploited. The dark side is that quantum computers will open the door to finding patterns that either do not actually exist, or if they did exist at one time, no longer do. In more technical terms, quantum computing may allow for a new level of unwarranted data mining and lead to further confusion regarding the role of nonstationarity.

ValueWalk's Raul Panganiban interviews George Mussalli, Chief Investment Officer and Head of Equity Research at PanAgora Asset Management. In this epispode, they discuss quant ESG as well as PanAgoras unique approach to it. The following is a computer generated transcript and may contain some errors. Q3 2020 hedge fund letters, conferences and more Interview . Read More

Any actual sequence of numbers, even one generated by a random process, will have certain statistical quirks. Physicist Richard Feynman used to make this point with reference to the first 767 digits of Pi, replicated below. Allegedly (but unconfirmed) he liked to reel off the first 761 digits, and then say 9-9-9-9-9 and so on.[1] If you only look at the first 767 digits the replication of six straight nines is clearly an anomaly a potential investment opportunity. In fact, there is no discernible pattern in the digits of Pi. Feynman was purposely making fun of data mining by focusing on the first 767 digits.

3 .1 4 1 5 9 2 6 5 3 5 8 9 7 9 3 2 3 8 4 6 2 6 4 3 3 8 3 2 7 9 5 0 2 8 8 4 1 9 7 1 6 9 3 9 9 3 7 5 1 0 5 8 2 0 9 7 4 9 4 4 5 9 2 3 0 7 8 1 6 4 0 6 2 8 6 2 0 8 9 9 8 6 2 8 0 3 4 8 2 5 3 4 2 1 1 7 0 6 7 9 8 2 1 4 8 0 8 6 5 1 3 2 8 2 3 0 6 6 4 7 0 9 3 8 4 4 6 0 9 5 5 0 5 8 2 2 3 1 7 2 5 3 5 9 4 0 8 1 2 8 4 8 1 1 1 7 4 5 0 2 8 4 1 0 2 7 0 1 9 3 8 5 2 1 1 0 5 5 5 9 6 4 4 6 2 2 9 4 8 9 5 4 9 3 0 3 8 1 9 6 4 4 2 8 8 1 0 9 7 5 6 6 5 9 3 3 4 4 6 1 2 8 4 7 5 6 4 8 2 3 3 7 8 6 7 8 3 1 6 5 2 7 1 2 0 1 9 0 9 1 4 5 6 4 8 5 6 6 9 2 3 4 6 0 3 4 8 6 1 0 4 5 4 3 2 6 6 4 8 2 1 3 3 9 3 6 0 7 2 6 0 2 4 9 1 4 1 2 7 3 7 2 4 5 8 7 0 0 6 6 0 6 3 1 5 5 8 8 1 7 4 8 8 1 5 2 0 9 2 0 9 6 2 8 2 9 2 5 4 0 9 1 7 1 5 3 6 4 3 6 7 8 9 2 5 9 0 3 6 0 0 1 1 3 3 0 5 3 0 5 4 8 8 2 0 4 6 6 5 2 1 3 8 4 1 4 6 9 5 1 9 4 1 5 1 1 6 0 9 4 3 3 0 5 7 2 7 0 3 6 5 7 5 9 5 9 1 9 5 3 0 9 2 1 8 6 1 1 7 3 8 1 9 3 2 6 1 1 7 9 3 1 0 5 1 1 8 5 4 8 0 7 4 4 6 2 3 7 9 9 6 2 7 4 9 5 6 7 3 5 1 8 8 5 7 5 2 7 2 4 8 9 1 2 2 7 9 3 8 1 8 3 0 1 1 9 4 9 1 2 9 8 3 3 6 7 3 3 6 2 4 4 0 6 5 6 6 4 3 0 8 6 0 2 1 3 9 4 9 4 6 3 9 5 2 2 4 7 3 7 1 9 0 7 0 2 1 7 9 8 6 0 9 4 3 7 0 2 7 7 0 5 3 9 2 1 7 1 7 6 2 9 3 1 7 6 7 5 2 3 8 4 6 7 4 8 1 8 4 6 7 6 6 9 4 0 5 1 3 2 0 0 0 5 6 8 1 2 7 1 4 5 2 6 3 5 6 0 8 2 7 7 8 5 7 7 1 3 4 2 7 5 7 7 8 9 6 0 9 1 7 3 6 3 7 1 7 8 7 2 1 4 6 8 4 4 0 9 0 1 2 2 4 9 5 3 4 3 0 1 4 6 5 4 9 5 8 5 3 7 1 0 5 0 7 9 2 2 7 9 6 8 9 2 5 8 9 2 3 5 4 2 0 1 9 9 5 6 1 1 2 1 2 9 0 2 1 9 6 0 8 6 4 0 3 4 4 1 8 1 5 9 8 1 3 6 2 9 7 7 4 7 7 1 3 0 9 9 6 0 5 1 8 7 0 7 2 1 1 3 4 9 9 9 9 9 9

When it comes to investing, there is only one sequence of historical returns. With sufficient computing power and with repeated torturing of the data, anomalies are certain to be detected. A good example is factor investing. The publication of a highly influential paper by Professors Eugene Fama and Kenneth French identified three systematic investment factors, which started an industry focused on searching for additional factors. Research by Arnott, Harvey, Kalesnik and Linnainmaa reports that by year-end 2018 an implausibly large 400 significant factors had been discovered. One wonders how many such anomalies quantum computers might find.

Factor investing is just one example among many. Richard Roll, a leading academic financial economist with in-depth knowledge of the anomalies literature has also been an active financial manager. Based on his experience Roll stated that his money management firms attempted to make money from numerous anomalies widely documented in the academic literature but failed to make a nickel.

The simple fact is that if you have machines that can look closely enough at any historical data set, they will find anomalies. For instance, what about the anomalous sequence 0123456789 in the expansion of Pi.? That anomaly can be found beginning at digit 17,387,594,880.

The digits of Pi may be random, but they are stationary. The process that generates the first million digits is the same as the one which generates the million digits beginning at one trillion. The same is not true of investing. Consider, for example, providing a computer the sequence of daily returns on Apple stock from the day the company went public to the present. The computer could sift through the returns looking for patterns, but this is almost certainly a fruitless endeavor. The company that generated those returns is far from stationary. In 1978, Apple was run by two young entrepreneurs and had total revenues of $0.0078 billion. By 2019, the company was run by a large, experienced, management team and had revenues of $274 billion, an increase of about 35,000 times. The statistical process generating those returns is almost certainly nonstationary due to fundamental changes in the company generating them. To a lesser extent, the same is true of nearly every listed company. The market is constantly in flux and the companies are constantly evolving as consumer demands, government regulation, and technology, among other things, continually change. It is hard to imagine that even if there were past patterns in stock prices that were more than data mining, they would persist for long due to nonstationarity.

In the finance arena, computers and artificial intelligence work by using their massive data processing skills to find patterns that humans may miss. But in a nonstationary world the ultimate financial risk is that by the time they are identified those patterns will be gone. As a result, computerized trading comes to resemble a dog chasing its tail. This leads to excessive trading and ever rising costs without delivering superior results on average. Quantum computing risks simply adding fuel. Of course, there are individual cases where specific quant funds make highly impressive returns, but that too could be an example of data mining. Given the large number of firms in the money management business, the probability that a few do extraordinarily well is essentially one.

These criticisms are not meant to imply that quantum computing has no role to play in finance. For instance, it has great potential to improve the simulation analyses involved in assessing risk. The point here is that it will not be a holy grail for improving investment performance.

Despite the drawbacks associated with data mining and nonstationarity, there is one area in which the potential for quantum computing is particularly bright marketing quantitative investment strategies. Selling quantitative investment has always been an art. It involves convincing people that the investment manager knows something that will make them money, but which is too complicated to explain to them and, in some cases, too complicated for the manager to understand. Quantum computing takes that sales pitch to a whole new level because virtually no one will be able to understand how the machine decided that a particular investment strategy is attractive.

This skeptics take is that quantum computing will have little impact on what is ultimately the source of successful investing allocating capital to companies that have particularly bright prospects for developing profitable business in a highly uncertain and non-stationary world. Perhaps at some future date a computer will development the business judgment to determine whether Teslas business prospects justify its current stock price. Until then being able to comb through historical data in search of obscure patterns at ever increasing rates is more likely to produce profits through the generation of management fees rather than the enhancement of investor returns.

[1] The Feynman story has been repeated so often that the sequence of 9s starting at digit 762 is now referred to as the Feynman point in the expansion of Pi.

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Quantum Computing And Investing - ValueWalk