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PRESS RELEASEConnecticut/December 18, 2023If Connecticut is afforded the opportunity to develop the most advanced technology in the worldtechnology that would save lives, create jobs, strengthen the economy, and revolutionize many industrieshow could it not vigorously pursue it?

That was the question that Rajeeb Hazra, an international quantum-computing expert, and the keynote speaker at Thursdays Imagining a Quantum Future event, posed to the audience of more than 150 academic, government, and industry leaders.

What gets me fired up is a future where the entire world benefits from novel developments, Hazra says. We could see cures for chronic diseases. Cancer and autism, and many other diseases, could be a thing of the past.

We could create batteries that last a lifetime, so that youd never have to stop to charge an electric vehicle, he continued. Quantum technology could solve problems that humanity, despite its best efforts, has not been able to solve.

Participants at the event learned how quantum technologies will be particularly valuable to Connecticut industries, including aerospace and advanced manufacturing, healthcare, and insurance and financial services. Leaders from each of those industries were present and helped lead breakout session discussions.

I think Connecticut, if you look at the recipe, has all of the ingredients in the right proportion to succeed, says Hazra, who is the president and CEO of Quantinuum, an international firm. Collectively I see people changing their question from Why Connecticut? to Why not Connecticut?

Hazra also emphasized the urgency to move forward quickly.

We have to be smart because the quantum future is closer than we think, he says. There is not an infinite window to make these decisions.

Connecticut Innovation Officer: This is Our Moment!

The effort to make Connecticut a national quantum technology hub is spearheaded by Quantum CT, a collaboration of academic, business, and government entities.

UConns President Radenka Maric, Vice President for Research, Innovation & Entrepreneurship Pamir Alpay, and Yale Universitys Vice Provost for Research Michael Crair, have all taken visible leadership positions on the initiative.

This effort was initiated by Dr. Maric some 20 months ago, because she recognized the vast potential of quantum technologies, Alpay said. Since then, the two universities have been working hand-in-hand to advance Connecticuts position as a center of excellence in quantum.

In May, the National Science Foundation awarded Quantum CT with a $1 million planning grant to build a network of partners in science, education, industry, government, and within the broader community, as a whole. At the end of 2024, the team plans to submit a phase-two proposal for a $160 million award to make Connecticut the hub for nations quantum technology.

This is our moment!, says Dan OKeefe, the commissioner designate of the Department of Economic and Community Development and Connecticuts chief innovation officer. Connecticut has the brainpower and the expertise to advance complicated projects, including those involving quantum technologies. The state has recovered from the pandemic, and is poised for something big. Now we need everyone rowing in the same direction, he says.

Technology Could Revolutionize Almost Every Industry

Imagining a Quantum Future was the first event of its kind put on in support of Quantum CT. It was organized jointly by Launc[H], the driving force behind Hartfords innovation ecosystem, the City of Hartford, the events lead sponsor, and UConn and Yale. Hosting it at the School of Business facility in Hartford was also strategic.

Quantum technologies could revolutionize business in virtually every industry, says David Souder, senior associate dean at the School of Business. We are committed to developing talent that is prepared to address these complex challenges.

Dr. Jeffrey Hines, UConn Healths Chief Diversity Officer, says quantum technology has the ability to benefit many previously marginalized communities, through workforce development, education, manufacturing and more. He believes that efforts being made to develop comprehensive workforce development and education strategies, through Quantum CT, offer tremendous opportunities to advance equity and inclusion in our state.

Hartford Mayor Luke Bronin, who is completing his eighth and final year in office, says that quantum technology has enormous potential to transform the world and Connecticuts industries. He says he is excited about the synergy between Yale and UConn.

Its a powerful partnership that marshals all the strengths of academics and industry to accelerate this work and position Connecticut at the forefront, he says.

Hartford Mayor-Elect Arunan Arulampalam also expressed his enthusiasm and support for advancing Hartfords position as a center of innovation. Were reclaiming the soul of this city!, he said, citing the fact that the first electric vehicle was developed and built in Hartford a century before the emergence of Tesla.

Crair, from Yale, says that the collegiate partnership has been mutually beneficial and will help the institutions recruit and retain the best educators, who seek environment of innovation and robust discovery.

Alpay, his UConn counterpart, says he is excited about the economic development opportunities that Quantum CT can generate, as well as its focus on developing new strategies to educate the next-generation workforce.

This is the technology of the future and we recognize the importance and opportunities of leading from the inception, he says.

Maric says she is pleased with the progress that the team has made so far, and remains excited for what is to come.

UConn is honored to join Yale as leaders in the effort to make Connecticut Americas accelerator by transforming a diverse, compact region into an economic development powerhouse using quantum tech, Maric says. Our event, Imagining a Quantum Future in Hartford generated tremendous excitement and helped to strengthen the partnerships that we will need to succeed.

SOURCE

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Insider Brief

As US legislation to fund quantum hangs in the balance, research advances may boost chances of quantums funding in government, insiders are telling Politico.

Earlier this month, researchers from Harvard University, along with QuEra Computing, MIT, and NIST/UMD, tackled one of the thorniest challenges in quantum information processing errors when they executed large-scale algorithms on an error-corrected quantum computer with 48 logical qubits and hundreds of entangling logical operations. For extremely sensitive quantum calculations that can be thrown off by a range of environmental interferences, this was a huge leap in error correction and a step toward creating quantum devices that can handle meaningful tasks that bog down classical computers.

IBM also reported on a quantum processor that improves managing of errors and touted a big push to designing and building quantum computers with more than 1,000 qubits.

Politico reports the news has not gone unnoticed in Washington D.C.

For that legislation to pass, the goal is for it to be as uncontroversial and as proven as possible, and a recent breakthrough certainly provides a useful talking point, Adam Kovacevich, founder and CEO of the Chamber of Progress, told Politico.

These reports may be critical because the federal government is debating the extension of the reauthorization of the National Quantum Initiative Act, which is currently up for its first five-year extension since the original bill was signed into law in 2018, Politico reports. The legislation partially funded the Harvard study, the political news site added.

Despite these advances, theres no guarantee the legislation to fund quantum will navigate the perilous journey through Congress. While the House Committee on Science, Space and Technology passed the bill in November the House of Representatives did not attach it to the National Defense Authorization Act. Politico reports that representatives could attach quantum spending to another spending bill next month.

A couple of hurdles seem to be blocking the passing of the reauthorization, according to Politico: partisan disagreements and the growing obsession with artificial intelligence.

Garnering attention for quantum in the current tech policy landscape dominated by AI remains an uphill battle, and navigating this environment to secure sufficient recognition and resources for quantum is proving a difficult task, Hodan Omaar, a senior policy analyst at the Information Technology and Innovation Foundation, told Politico, but added, These sorts of breakthroughs dont hurt.

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Recent Research Advances Likely to Boost Government Support of Quantum - The Quantum Insider

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Quantum computing is on the cusp of reshaping the landscape of artificial intelligence (AI) in profound ways, ushering in a new era of capabilities and possibilities. Over the next decade, we can expect to witness a transformation in AI applications fueled by the quantum revolution. If youre looking to know how quantum computing will affect artificial intelligence applications, stay tuned.

In this brief exploration, we will delve into three key ways in which quantum computing is poised to reshape AI, offering a glimpse into the future of these groundbreaking technologies.

We have listed three ways in which quantum computing affects artificial intelligence applications. Take a look:

Quantum computing holds immense potential to revolutionize ML and AI algorithms in several profound ways. In this extended examination, we will delve deeper into these enhancements, providing additional case studies and examples of potential applications, and also discuss some of the challenges and limitations of quantum machine learning (QML).

To delve deeper into advanced AI concepts, explore our complete guide on quantum artificial intelligence.

Quantum computers leverage the principles of superposition and entanglement to process data exponentially faster than classical computers. This speed is especially critical in ML, where tasks such as training complex models and performing large-scale simulations can be highly time-consuming.

Grovers algorithm, for instance, showcases quantum computings potential by searching unsorted databases quadratically faster than classical algorithms. This capability could significantly speed up data retrieval tasks in AI systems.

Quantum computing has the potential to efficiently manage models that are currently too complex for classical computers to handle. This includes deep learning networks with an unprecedented number of layers and nodes.

This breakthrough could lead to the development of more advanced AI models capable of learning from even larger datasets and making highly accurate predictions. These models might be particularly advantageous in areas like image recognition, natural language understanding, and autonomous decision-making systems.

Two critical aspects of quantum physics, superposition, and entanglement, contribute significantly to the enhanced computing power of quantum computers. Superposition allows a quantum bit (qubit) to be in a combination of states at once, while entanglement enables particles to remain interconnected regardless of the distance between them, allowing instantaneous interactions.

Quantum computing and ML can significantly boost each other. It is not just about speed; its also about the ability to create models that reflect complex conditions far better than current models. This is especially beneficial in areas like financial portfolio optimization, fluid dynamics simulations, and material design.

Quantum computing holds the potential to revolutionize the way complex optimization problems are solved across various industries. This is primarily due to its ability to process and analyze large datasets much faster than classical computers, as well as its unique approach to handling data through quantum mechanics principles.

Quantum entanglement is a phenomenon where pairs or groups of qubits interact in such a way that the state of one qubit is directly related to the state of another, regardless of the distance between them. This interconnectedness enables high-level correlation and parallelism in computations.

In optimization problems, entanglement allows for more efficient coordination of information across different parts of a system, enabling the quantum computer to find correlations and patterns that are not easily discernible with classical computing methods.

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Quantum computers can perform certain types of search operations much faster than classical computers, thanks to algorithms like Grovers algorithm. This is particularly beneficial in optimization problems, where the solution involves searching through a vast number of possibilities.

Quantum computers are well-suited for dealing with problems involving a large number of variables and high-dimensional spaces, which are common in complex optimization tasks. Their ability to handle these types of problems can lead to more efficient solutions than those achievable with classical techniques.

Quantum algorithms, in some cases, can provide exponential speedups over their classical counterparts. This is particularly relevant in optimization problems where traditional algorithms may struggle with the complexity or size of the data.

This quantum computing technique is used specifically for solving optimization problems. It works by encoding the problem into a quantum system and then gradually evolving this system to its lowest energy state, which corresponds to the optimal solution.

Quantum computing significantly impacts artificial intelligence applications in RL by enhancing the learning processs speed and efficiency. The unique capabilities of quantum computing, such as superposition and entanglement, allow RL algorithms to explore multiple solutions simultaneously, leading to faster learning compared to traditional methods.

A significant advancement in quantum computing for reinforcement learning is the development of hybrid systems that combine quantum and classical computing. These systems use quantum computing for trial-and-error exploration in RL, while a classical computer provides feedback or rewards based on the AI agents performance. This approach has been shown to speed up the learning process of an AI agent by over 60% in certain scenarios.

Quantum reinforcement learning (QRL) can potentially require fewer training steps to reach convergence compared to traditional RL methods. This efficiency is particularly beneficial in applications where data collection is resource-intensive or difficult, such as in autonomous systems and healthcare.

Research has focused on finding the most suitable quantum architectures and learning algorithms for RL tasks. For instance, selecting a hardware-efficient parametrized quantum circuit (PQC) and refining classical algorithms like REINFORCE to work with quantum platforms have been crucial steps. These advancements contribute to successfully training RL agents on quantum devices, albeit with some adaptations to fit the constraints of current quantum hardware.

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Lets delve into each of these eight real-life applications in greater depth to appreciate the profound impact quantum computing is set to exert:

Quantum computing offers a quantum leap in the field of pharmaceuticals. By leveraging quantum algorithms, it can significantly accelerate the complex process of molecular simulation, expediting the analysis of intricate molecular structures and interactions essential for drug discovery.

This revolutionary speed-up enables researchers to explore a vast chemical space, leading to the rapid identification and development of new drugs and treatments for a multitude of diseases, ultimately improving global healthcare.

Financial institutions worldwide stand to gain immensely from quantum computings computational prowess. Its capacity to process vast volumes of financial data with unprecedented speed and precision can transform asset allocation strategies, revolutionize risk assessment models, and fortify fraud detection mechanisms.

This quantum advantage empowers financial professionals with more accurate insights into market trends, enhancing decision-making and risk management in the financial sector.

The intricacies of modern transportation systems and logistics networks demand sophisticated optimization solutions. Classical computers often struggle to tackle the complexity of these problems efficiently.

Quantum algorithms, however, excel in handling numerous variables simultaneously, making them indispensable for solving intricate route optimization challenges. This, in turn, leads to reduced congestion, improved urban mobility, and enhanced supply chain efficiency, benefitting both cities and businesses.

Quantum computing offers a ray of hope in addressing the pressing issue of climate change. Its capacity to simulate the complexities of environmental systems with high precision promises the development of more accurate climate models.

These advanced models provide invaluable insights into climate dynamics, empowering policymakers to formulate more effective strategies for mitigating the effects of climate change and preserving the environment for future generations.

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Quantum computings prowess extends to the realm of energy optimization. It can simulate and optimize energy distribution networks, paving the way for increased energy efficiency and reduced operational costs across various industries and power grids.

This transformative application has far-reaching implications for sustainable energy practices, contributing to a greener and more environmentally conscious future.

Quantum computing plays a pivotal role in the discovery of groundbreaking materials with tailor-made properties. Through precise atomic-level simulations, it facilitates the development of materials optimized for specific applications.

These include high-performance batteries for renewable energy storage, advanced materials for cutting-edge electronics, and innovative materials for aerospace and engineering, driving innovation across a wide array of industries.

Quantum computing presents both challenges and opportunities in the realm of cybersecurity. While its immense processing power threatens existing encryption methods, it also necessitates the development of quantum-resistant encryption techniques.

Quantum computing can also contribute to the creation of more robust cryptographic protocols, bolstering cybersecurity across industries, protecting sensitive data, and ensuring the integrity of digital systems.

In essence, these applications underscore the extraordinary potential of quantum computing to catalyze innovation and transformation across diverse sectors of our global economy.

Although quantum computing is affecting artificial intelligence applications in positive ways, it also faces several limitations that are important to consider:

One of the major challenges of quantum computing is the current limitations in hardware. Quantum computers are limited in terms of their size and the number of qubits they can support.

This constrains the complexity of the problems that can be solved and makes it difficult to scale the technology. As quantum computing evolves, addressing these hardware limitations will be crucial for its broader application in AI and other fields.

Quantum computing is more prone to errors compared to classical computing due to the delicate nature of qubits. Moreover, developing robust error correction techniques is critical for creating reliable quantum computing systems.

This is a significant area of research in quantum computing, as the effectiveness of quantum algorithms depends heavily on the accuracy of quantum operations.

Quantum computing requires a completely different set of algorithms and programming techniques compared to classical computing. This complexity makes it challenging for developers to adapt and limits the number of professionals who can effectively work with quantum technology.

The distinct nature of quantum programming, involving quantum gates and the probabilistic nature of qubit states, requires a new mindset and understanding.

Quantum computing poses potential risks to cybersecurity. Furthermore, its ability to process complex algorithms at high speed could potentially break many of the cryptographic algorithms currently used to secure data and communications.

Therefore, the development of new quantum-resistant cryptographic algorithms is essential.

The absence of universally accepted standards in quantum computing hinders collaboration and idea-sharing among researchers and developers. Moreover, establishing such standards will be essential for the development of a robust and scalable quantum computing industry.

Despite these challenges, quantum computing holds the promise of transformative outcomes. Furthermore, it includes increased computational power, improved efficiency, new scientific discoveries, enhanced cybersecurity, and increased innovation.

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The future developments in quantum computing are expected to focus on several key areas, each addressing current limitations and expanding the potential applications of this technology:

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As quantum computing continues to advance at a rapid pace, its impact on artificial intelligence applications in the coming decade cannot be overstated. The synergy between quantum computing and AI is set to drive monumental changes. Additionally, this ranges from supercharged data analysis and optimization to the development of more sophisticated AI models.

With each passing year, we edge closer to realizing the full potential of this transformative partnership. Moreover, it promises breakthroughs that will not only reshape industries but also broaden the horizons of what AI can achieve. The next decade promises to be an exciting journey as we witness the evolution of quantum-powered AI. Finally, this opens doors to solutions for some of humanitys most complex challenges.

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3 Ways Quantum Computing Will Affect Artificial Intelligence Applications in the Next Decade - AMBCrypto Blog

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Dec. 20, 2023 As industrial computing needs grow, the size and energy consumption of the hardware needed to keep up with those needs grows as well. A possible solution to this dilemma could be found in superconducting materials, which can reduce that energy consumption exponentially. Imagine cooling a giant data center full of constantly running servers down to nearly absolute zero, enabling large-scale computation with incredible energy efficiency.

Physicists at the University of Washington and the U.S. Department of Energys (DOE) Argonne National Laboratory have made a discovery that could help enable this more efficient future. Researchers have found a superconducting material that is uniquely sensitive to outside stimuli, enabling the superconducting properties to be enhanced or suppressed at will. This enables new opportunities for energy-efficient switchable superconducting circuits. The paper was published in Science Advances.

Superconductivity is a quantum mechanical phase of matter in which an electrical current can flow through a material with zero resistance. This leads to perfect electronic transport efficiency. Superconductors are used in the most powerful electromagnets for advanced technologies such as magnetic resonance imaging, particle accelerators, fusion reactors and even levitating trains. Superconductors have also found uses in quantum computing.

Todays electronics use semiconducting transistors to quickly switch electric currents on and off, creating the binary ones and zeroes used in information processing. As these currents must flow through materials with finite electrical resistance, some of the energy is wasted as heat. This is why your computer heats up over time. The low temperatures needed for superconductivity, usually more than 200 degrees Fahrenheit below freezing, makes those materials impractical for hand-held devices. However, they could conceivably be useful on an industrial scale.

The research team, led by Shua Sanchez of the University of Washington (now at the Massachusetts Institute of Technology), examined an unusual superconducting material with exceptional tunability. This crystal is made of flat sheets of ferromagnetic europium atoms sandwiched between superconducting layers of iron, cobalt and arsenic atoms. Finding ferromagnetism and superconductivity together in nature is extremely rare, according to Sanchez, as one phase usually overpowers the other.

It is actually a very uncomfortable situation for the superconducting layers, as they are pierced by the magnetic fields from the surrounding europium atoms, Sanchez said. This weakens the superconductivity and results in a finite electrical resistance.

To understand the interaction of these phases, Sanchez spent a year as a resident at one of the nations leading X-ray light sources, the Advanced Photon Source (APS), a DOE Office of Science user facility at Argonne. While there he was supported by DOEs Science Graduate Student Research program. Working with physicists at APS beamlines 4-ID and 6-ID, Sanchez developed a comprehensive characterization platform capable of probing microscopic details of complex materials.

Using a combination of X-ray techniques, Sanchez and his collaborators were able to show that applying a magnetic field to the crystal can reorient the europium magnetic field lines to run parallel to the superconducting layers. This removes their antagonistic effects and causes a zero-resistance state to emerge. Using electrical measurements and X-ray scattering techniques, scientists were able to confirm that they could control the behavior of the material.

The nature of independent parameters controlling superconductivity is quite fascinating, as one could map out a complete method of controlling this effect, said Argonnes Philip Ryan, a co-author on the paper. This potential posits several fascinating ideas including the ability to regulate field sensitivity for quantum devices.

The team then applied stresses to the crystal with interesting results. They found the superconductivity could be either boosted enough to overcome the magnetism even without re-orienting the field or weakened enough that the magnetic reorientation could no longer produce the zero-resistance state. This additional parameter allows for the materials sensitivity to magnetism to be controlled and customized.

This material is exciting because you have a close competition between multiple phases, and by applying a small stress or magnetic field, you can boost one phase over the other to turn the superconductivity on and off, Sanchez said. The vast majority of superconductors arent nearly as easily switchable.

About the Advanced Photon Source

The U. S. Department of Energy Office of Sciences Advanced Photon Source (APS) at Argonne National Laboratory is one of the worlds most productive X-ray light source facilities. The APS provides high-brightness X-ray beams to a diverse community of researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. These X-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nations economic, technological, and physical well-being. Each year, more than 5,000 researchers use the APS to produce over 2,000 publications detailing impactful discoveries, and solve more vital biological protein structures than users of any other X-ray light source research facility. APS scientists and engineers innovate technology that is at the heart of advancing accelerator and light-source operations. This includes the insertion devices that produce extreme-brightness X-rays prized by researchers, lenses that focus the X-rays down to a few nanometers, instrumentation that maximizes the way the X-rays interact with samples being studied, and software that gathers and manages the massive quantity of data resulting from discovery research at the APS.

This research used resources of the Advanced Photon Source, a U.S. DOE Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357.

About Argonne National Laboratory

Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nations first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance Americas scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energys Office of Science.

Source: Shua Sanchez And Andre Salles, Argonne

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As your credit card is scanned one final time this holiday season, say thanks to prime numbers for keeping the checkout queues short and your money safe. Well, most of the time anyway. Much of the cryptography that goes into beating credit-card fraud comes down to 3,5,7, etc, or integers that can only be divided into themselves and 1. Banks randomly generate two huge primessay, 150 digits longand multiply them to encrypt payment authorization from the microchip of your card to the point-of-sale terminal.

As your credit card is scanned one final time this holiday season, say thanks to prime numbers for keeping the checkout queues short and your money safe. Well, most of the time anyway. Much of the cryptography that goes into beating credit-card fraud comes down to 3,5,7, etc, or integers that can only be divided into themselves and 1. Banks randomly generate two huge primessay, 150 digits longand multiply them to encrypt payment authorization from the microchip of your card to the point-of-sale terminal.

Even supercomputers cant easily decipher the original numbers because the time required to run any of the known algorithms increases exponentially with their length. A 250-digit number that was part of a 1991 factorization challenge was finally broken down into a product of two primes in 2020. On a single advanced computer running non-stop, the calculations would take 2,700 years.

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Even supercomputers cant easily decipher the original numbers because the time required to run any of the known algorithms increases exponentially with their length. A 250-digit number that was part of a 1991 factorization challenge was finally broken down into a product of two primes in 2020. On a single advanced computer running non-stop, the calculations would take 2,700 years.

Rivest-Shamir-Adleman (RSA) private keys generated with the help of large numbers let bank affix a unique, tamper-proof digital signature via microchips embedded in cards. With these replacing magnetic strips, the menace of counterfeiting has gone down. Payment scams are now more likely in e-commerce deals. However, a new challenge is emerging that could begin to erode the protection offered by prime numbers, perhaps by decade-end.

The first hint of trouble came at the start of the millennium. A team of scientists at IBM exploited the mysterious interplay of subatomic matter and energy to run calculations that would be impossible on a classical computer. Their primitive quantum computer figured out that 15 was a product of 3 and 5. A subsequent experiment in 2012 split 21 into 3 and 7. While every middle-schooler knows how to break down small integers like 15 and 21, these were the first demonstrations of Shors algorithm, a method of quantum factorization that does not get exponentially more time-consuming as the number gets bigger. In August, Oded Regev of New York University proposed what many consider the first big improvement to Peter Shors 1994 technique. If it works, the time taken to decode complex ciphers may shorten. By 2030, a $1 billion quantum computer may be able to break RSA Laboratories widely used 2048-bit encryption by factoring a 617-digit number in a few hours, according to a 2016 estimate by the National Institute of Standards and Technology in Maryland. NIST has come up with new protocols that will be resistant to quantum computers, but what if the threat arrives before the weaponry to ward it off has been adopted?

Retail losses may be kept to manageable levels, at least for a while. But a wholesale quantum heist would be catastrophic. The security of worldwide interbank payments may be compromised if the digital signatures authorizing release of funds lose their sanctity. Scammers already have a blueprint in the $81 million theft from Bangladeshs accounts with the Federal Reserve Bank of New York in 2016.

It isnt just the security of existing products thats at stake; innovative new payment instruments will be affected, too. Monetary authorities are experimenting with paperless cash. The Bank for International Settlements estimates that by 2030, there may be 15 central bank digital currencies (CBDCs) in retail circulation.

Tourbillon, a recent BIS project, has shown that the cash-like privacy that users will expect of these instruments may be realizable. The so-called blind signature protocol, invented by privacy pioneer David Chaum in 1982, may be enough to ensure that payers dont reveal their identities to anyone. Even the central bank will only check that the eCash that comes to it for verification has its signature and not been spent before. Payments made using such highly private CBDCs may also be fast and able to handle peak demand. However, this is only true as long as the RSA encryption technology is strong enough to keep malicious actors at bay. Introduce quantum-safe cryptography into the equation, and the cost to users increases: A one-second payment cycle stretches to five; transactions per second drop by a factor of 200. More experimentation is needed. If it turns out that a central banks virtual signature on CBDC tokens is not impervious to quantum counterfeitingor can only be foolproofed by slowing payments downthen ordinary people are going to reject them.

As the ChatGPT-induced revolution in generative AI has shown, meaningful breakthroughs can elude a field for decades. But once they do occur, they can multiply at an overwhelming speed. Quantum computing may be no different. Prime numbers have served the internet age well, but the private sector and public authorities cannot take their continued guardianship for granted. bloomberg

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Quantum computing will make online heists likelier than we can fathom | Mint - Mint

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