Archive for the ‘Quantum Computing’ Category

Unlocking the quantum future – MIT News

Quantum computing is the next frontier for faster and more powerful computing technologies. It has the potential to better optimize routes for shipping and delivery, speed up battery development for electric vehicles, and more accurately predict trends in financial markets. But to unlock the quantum future, scientists and engineers need to solve outstanding technical challenges while continuing to explore new applications.

One place where theyre working towards this future is the MIT Interdisciplinary Quantum Hackathon, or iQuHACK for short (pronounced i-quack, like a duck). Each year, a community of quhackers (quantum hackers) gathers at iQuHACK to work on quantum computing projects using real quantum computers and simulators. This year, the hackathon was held both in-person at MIT and online over three days in February.

Quhackers worked in teams to advance the capability of quantum computers and to investigate promising applications. Collectively, they tackled a wide range of projects, such as running a quantum-powered dating service, building an organ donor matching app, and breaking into quantum vaults. While working, quhackers could consult with scientists and engineers in attendance from sponsoring companies. Many sponsors also received feedback and ideas from quhackers to help improve their quantum platforms.

But organizing iQuHACK 2024 was no easy feat. Co-chairs Alessandro Buzzi and Daniela Zaidenberg led a committee of nine members to hold the largest iQuHACK yet. It wouldnt have been possible without them, Buzzi said. The hackathon hosted 260 in-person quhackers and 1,000 remote quhackers, representing 77 countries in total. More than 20 scientists and engineers from sponsoring companies also attended in person as mentors for quhackers.

Each team of quhackers tackled one of 10 challenges posed by the hackathons eight major sponsoring companies. Some challenges asked quhackers to improve computing performance, such as by making quantum algorithms faster and more accurate. Other challenges asked quhackers to explore applying quantum computing to other fields, such as finance and machine learning. The sponsors worked with the iQuHACK committee to craft creative challenges with industry relevance and societal impact. We wanted people to be able to address an interesting challenge [that has] applications in the real world, says Zaidenberg.

One team of quhackers looked for potential quantum applications and found one close to home: dating. A team member, Liam Kronman, had previously built dating apps but disliked that matching algorithms for normal classical computers require [an overly] strict setup. With these classical algorithms, people must be split into two groups for example, men and women and matches can only be made between these groups. But with quantum computers, matching algorithms are more flexible and can consider all possible combinations, enabling the inclusion of multiple genders and gender preferences.

Kronman and his team members leveraged these quantum algorithms to build a quantum-powered dating platform called MITqute (pronounced meet cute). To date, the platform has matched at least 240 people from the iQuHACK and MIT undergrad communities. In a follow-up survey, 13 out of 41 respondents reported having talked with their match, with at least two pairs setting up dates. I really lucked out with this one, one respondent wrote.

Another team of quhackers also based their project on quantum matching algorithms but instead leveraged the algorithms power for medical care. The team built a mobile app that matches organ donors to patients, earning them the hackathons top social impact award.

But they almost didnt go through with their project. At one point, we were considering scrapping the whole thing because we thought we couldnt implement the algorithm, says Alma Alex, one of the developers. After talking with their hackathon mentor for advice, though, the team learned that another group was working on a similar type of project incidentally, the MITqute team. Knowing that others were tackling the same problem inspired them to persevere.

A sense of community also helped to motivate other quhackers. For one of the challenges, quhackers were tasked with hacking into 13 virtual quantum vaults. Teams could see each others progress on each vault in real time on a leaderboard, and this knowledge informed their strategies. When the first vault was successfully hacked by a team, progress from many other teams spiked on that vault and slowed down on others, says Daiwei Zhu, a quantum applications scientist at IonQ and one of the challenges two architects.

The vault challenge may appear to be just a fun series of puzzles, but the solutions can be used in quantum computers to improve their efficiency and accuracy. To hack into a vault, quhackers had to first figure out its secret key an unknown quantum state using a maximum of 20 probing tests. Then, they had to change the keys state to a target state. These types of characterizations and modifications of quantum states are fundamental for quantum computers to work, says Jason Iaconis, a quantum applications engineer at IonQ and the challenges other architect.

But the best way to characterize and modify states is not yet clear. Some of the [vaults] we [didnt] even know how to solve ourselves, Zhu says. At the end of the hackathon, six vaults had at least one team mostly hack into them. (In the quantum world where gray areas exist, its possible to partly hack into a vault.)

The community of scientists and engineers formed at iQuHACK persists beyond the weekend, and many members continue to grow the community outside the hackathon. Inspired quhackers have gone on to start their own quantum computing clubs at their universities. A few years ago, a group of undergraduate quhackers from different universities formed a Quantum Coalition that now hosts their own quantum hackathons. Its crazy to see how the hackathon itself spreads and how many people start their own initiatives, co-chair Zaidenberg says.

The three-day hackathon opened with a keynote from MIT Professor Will Oliver, which included an overview of basic quantum computing concepts, current challenges, and computing technologies. Following that were industry talks and a panel of six industry and academic quantum experts, including MIT Professor Peter Shor, who is known for developing one of the most famous quantum algorithms. The panelists discussed current challenges, future applications, the importance of collaboration, and the need for ample testing.

Later, sponsors held technical workshops where quhackers could learn the nitty-gritty details of programming on specific quantum platforms. Day one closed out with a talk by research scientist Xinghui Yin on the role of quantum technology at LIGO, the Laser Interferometer Gravitational-Wave Observatory that first detected gravitational waves. The next day, the hackathons challenges were announced at 10 a.m., and hacking kicked off at the MIT InnovationHQ. In the afternoon, attendees could also tour MIT quantum computing labs.

Hacking continued overnight at the MIT Museum and ended back at MIT iHQ at 10 a.m. on the final day. Quhackers then presented their projects to panels of judges. Afterward, industry speakers gave lightning talks about each of their companys latest quantum technologies and future directions. The hackathon ended with a closing ceremony, where sponsors announced the awards for each of the 10 challenges.

The hackathon was captured in a three-part video by Albert Figurt, a resident artist at MIT. Figurt shot and edited the footage in parallel with the hackathon. Each part represented one day of the hackathon and was released on the subsequent day.

Throughout the weekend, quhackers and sponsors consistently praised the hackathons execution and atmosphere. That was amazing never felt so much better, one of the best hackathons I did from over 30 hackathons I attended, Abdullah Kazi, a quhacker, wrote on the iQuHACK Slack.

Ultimately, [we wanted to] help people to meet each other, co-chair Buzzi says. The impact [of iQuHACK] is scientific in some way, but its very human at the most important level.

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Unlocking the quantum future - MIT News

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Verifying the Work of Quantum Computers – Caltech

Quantum computers of the future may ultimately outperform their classical counterparts to solve intractable problems in computer science, medicine, business, chemistry, physics, and other fields. But the machines are not there yet: They are riddled with inherent errors, which researchers are actively working to reduce. One way to study these errors is to use classical computers to simulate the quantum systems and verify their accuracy. The only catch is that as quantum machines become increasingly complex, running simulations of them on traditional computers would take years or longer.

Now, Caltech researchers have invented a new method by which classical computers can measure the error rates of quantum machines without having to fully simulate them. The team describes the method in a paper in the journal Nature.

"In a perfect world, we want to reduce these errors. That's the dream of our field," says Adam Shaw, lead author of the study and a graduate student who works in the laboratory of Manuel Endres, professor of physics at Caltech. "But in the meantime, we need to better understand the errors facing our system, so we can work to mitigate them. That motivated us to come up with a new approach for estimating the success of our system."

In the new study, the team performed experiments using a type of simple quantum computer known as a quantum simulator. Quantum simulators are more limited in scope than current rudimentary quantum computers and are tailored for specific tasks. The group's simulator is made up of individually controlled Rydberg atomsatoms in highly excited stateswhich they manipulate using lasers.

One key feature of the simulator, and of all quantum computers, is entanglementa phenomenon in which certain atoms become connected to each other without actually touching. When quantum computers work on a problem, entanglement is naturally built up in the system, invisibly connecting the atoms. Last year, Endres, Shaw, and colleagues revealed that as entanglement grows, those connections spread out in a chaotic or random fashion, meaning that small perturbations lead to big changes in the same way that a butterfly's flapping wings could theoretically affect global weather patterns.

This increasing complexity is believed to be what gives quantum computers the power to solve certain types of problems much faster than classical computers, such as those in cryptography in which large numbers must be quickly factored.

But once the machines reach a certain number of connected atoms, or qubits, they can no longer be simulated using classical computers. "When you get past 30 qubits, things get crazy," Shaw says. "The more qubits and entanglement you have, the more complex the calculations are."

The quantum simulator in the new study has 60 qubits, which Shaw says puts it in a regime that is impossible to simulate exactly. "It becomes a catch-22. We want to study a regime that is hard for classical computers to work in, but still rely on those classical computers to tell if our quantum simulator is correct." To meet the challenge, Shaw and colleagues took a new approach, running classical computer simulations that allow for different amounts of entanglement. Shaw likens this to painting with brushes of different size.

"Let's say our quantum computer is painting the Mona Lisa as an analogy," he says. "The quantum computer can paint very efficiently and, in theory, perfectly, but it makes errors that smear out the paint in parts of the painting. It's like the quantum computer has shaky hands. To quantify these errors, we want our classical computer to simulate what the quantum computer has done, but our Mona Lisa would be too complex for it. It's as if the classical computers only have giant brushes or rollers and can't capture the finer details.

"Instead, we have many classical computers paint the same thing with progressively finer and finer brushes, and then we squint our eyes and estimate what it would have looked like if they were perfect. Then we use that to compare against the quantum computer and estimate its errors. With many cross-checks, we were able to show this squinting' is mathematically sound and gives the answer quite accurately."

The researchers estimated that their 60-qubit quantum simulator operates with an error rate of 91 percent (or an accuracy rate of 9 percent). That may sound low, but it is, in fact, relatively high for the state of the field. For reference, the 2019 Google experiment, in which the team claimed their quantum computer outperformed classical computers, had an accuracy of 0.3 percent (though it was a different type of system than the one in this study).

Shaw says: "We now have a benchmark for analyzing the errors in quantum computing systems. That means that as we make improvements to the hardware, we can measure how well the improvements worked. Plus, with this new benchmark, we can also measure how much entanglement is involved in a quantum simulation, another metric of its success."

The Nature paper titled "Benchmarking highly entangled states on a 60-atom analog quantum simulator" was funded by the National Science Foundation (partially via Caltech's Institute for Quantum Information and Matter, or IQIM), the Defense Advanced Research Projects Agency (DARPA), the Army Research Office, the U.S. Department of Energy's Quantum Systems Accelerator, the Troesh postdoctoral fellowship, the German National Academy of Sciences Leopoldina, and Caltech's Walter Burke Institute for Theoretical Physics. Other Caltech authors include former postdocs Joonhee Choi and Pascal Scholl; Ran Finkelstein, Troesh Postdoctoral Scholar Research Associate in Physics; and Andreas Elben, Sherman Fairchild Postdoctoral Scholar Research Associate in Theoretical Physics. Zhuo Chen, Daniel Mark, and Soonwon Choi (BS '12) of MIT are also authors.

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Quantum Computing Could Destroy Bitcoin in 27 Years – BeInCrypto

Quantum computing is a revolutionary force with the potential to redefine industries, including the cryptocurrency market. For this reason, Bitcoin, the largest crypto by market capitalization at $1.27 trillion, stands at a crossroads.

With its reliance on the Proof-of-Work (POW) consensus protocol and Elliptic Curve Cryptography (ECC) for encryption, Bitcoin faces significant vulnerabilities against quantum computing.

The POW mechanism, integral to Bitcoins operation, involves miners solving complex mathematical problems to validate transactions and secure the network. However, quantum computing, with its ability to perform calculations at unprecedented speeds, threatens to disrupt this balance.

Quantum algorithms like Grovers could theoretically solve these problems much faster than classical computers. Therefore, this technology has the potential to centralize mining power and undermine the decentralized ethos of Bitcoin.

Bitcoin network hash rate using the most current value against aquantum computingtechnology, increasing over time at the same rate, as dictated by Moores Law, gives an estimated timeframe of approximately 27years until asinglequantum computer will be capable of completely out-mining the rest of the network, and hence be able to take over complete control of it, Dan A.Bard, Teaching Staff at theUniversity of Kent, wrote.

Furthermore, Bitcoins ECC encryption, a staple for securing wallet addresses, is also at risk. Quantum computers could one day use Shors algorithm to break ECC, exposing Bitcoin transactions to potential security breaches.

This vulnerability extends particularly to legacy addresses, which include a significant portion of Bitcoins founder, Satoshi Nakamotos holdings.

Once the public key is revealed, Shors algorithm adapted for ECDSA could be run on an ideal quantum computer to find the public key in polynomial time. Classically, finding a solution would be super-polynomial, orders of magnitude slower Polynomial time is potentially feasible, and it is conjectured that, eventually, ECDSA will be breakable by quantum computers,researchers at Acheron Trading wrote.

Despite these challenges, the immediate threat remains theoretical. Current quantum computing capabilities, as demonstrated by the largest Grover search to date using six qubits, are far from the scale required to disrupt Bitcoin mining or break ECC encryption effectively. However, the potential for quantum advantage, a state where quantum computers outperform their classical counterparts in specific tasks, looms on the horizon.

The Bitcoin community appears unlikely to shift from POW to alternative consensus mechanisms like Proof-of-Stake (POS). Even cryptographer Adam Back stated that PoS cryptocurrencies lack immutability, decentralization, and the verifiable, significant cost of production, highlighting their fundamental differences from Bitcoin.

Being hard money, immutable, decentralized, and verifiably costly to produce. The tech is structured to make that economically stable, and actually hard to modify. PoS coins have none of those properties. they also have a CEO, and dozens of competitors. There is only one Bitcoin, Back argued.

This resistance to change reflects the importance of proactive measures to safeguard the network against future quantum threats.

Read more: Proof of Work and Proof of Stake Explained

The path forward involves a delicate balance between maintaining Bitcoins foundational principles and adapting to technologies like quantum computing. Upgrading encryption methods and exploring quantum-resistant algorithms are critical steps to ensure Bitcoins resilience. The transition to quantum-safe cryptography will protect against immediate threats and secure the network against future advancements in quantum computing.

Disclaimer

In adherence to the Trust Project guidelines, BeInCrypto is committed to unbiased, transparent reporting. This news article aims to provide accurate, timely information. However, readers are advised to verify facts independently and consult with a professional before making any decisions based on this content. Please note that ourTerms and Conditions,Privacy Policy, andDisclaimershave been updated.

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Surviving the quantum apocalypse with fully homomorphic encryption – Help Net Security

In the past few years, an increasing number of tech companies, organizations, and even governments have been working on one of the next big things in the tech world: successfully building quantum computers.

These actors see a lot of potential in the technology. Quantum computing spreads across a wide range of disciplines both on the hardware research and application development fronts, including elements of computer science, physics, and mathematics. The goal is to combine these subjects to create a computer that utilizes quantum mechanics to solve complex problems faster than on classical computers.

Despite this description evoking images and scenarios fit for a sci-fi blockbuster, it is still hard to pinpoint what a quantum computer would do. Indeed, it seems that the only major application which people have identified is that of cryptanalysis.

Quantum computing has the potential to break cryptosystems that are the foundations of the technology protecting the privacy of data and information created and shared every day. When (and if) an applicable quantum computer is created, we will need to upgrade all our digital security protocols.

A traditional (digital) computer processes zeros and ones, so called bits. These, to a first order approximation, are represented as on/off electrical signals. A quantum computer, though, processes quantum states; these are units that can be thought of as being both zero and one at the same time. Such a state is called a quantum bit, or qubit.

If you hold n bits in a traditional computer then these n bits can represent any number between zero and 2^n-1, but a single bit can only represent one number at a time. If you had n qubits, then the quantum computer can represent EVERY number between 0 and 2^n-1 simultaneously.

The physics of quantum phenomena is counter-intuitive. For example, two qubits can be entangled so that even though they can be separated by a large distance, an operation performed on one of the entangled qubits can have an instantaneous effect on the other qubit.

This is where the privacy concern around quantum computers comes from: they not only store data differently, but also process it differently, giving users a very different form of computational model. With this model, quantum computers could be faster than traditional ones with regards to a few known tasks: unluckily, the two main tasks which quantum computers are good at are factoring large numbers and solving so-called discrete logarithm problems. I say unluckily, as it is precisely these two hard mathematical problems which lie at the base of all current security protocols on the internet.

The ability of a quantum system to solve these two mathematical problems will break the internet and all the systems we use day to day. The advent of a quantum computer and its effect on cybersecurity and data privacy is often dubbed the quantum apocalypse.

Thankfully, the advent of a suitably powerful quantum computer capable of breaking current cryptographic solutions does not yet seem to be on the horizon. But organizations and businesses that truly care about the privacy of their users and customers should start preparing for the worst by looking to integrate existing technologies and solutions in their operations and processes.

There are currently two distinct approaches to face an impending quantum apocalypse. The first uses the physics of quantum mechanics itself and is called Quantum Key Distribution (QKD). However, QKD only really solves the problem of key distribution, and it requires dedicated quantum connections between the parties. As such, it is not scalable to solve the problems of internet security; instead, it is most suited to private connections between two fixed government buildings. It is impossible to build internet-scale, end-to-end encrypted systems using QKD.

The second solution is to utilize classical cryptography but base it on mathematical problems for which we do not believe a quantum computer gives any advantage: this is the area of post-quantum cryptography (PQC). PQC algorithms are designed to be essentially drop-in replacements for existing algorithms, which would not require many changes in infrastructure or computing capabilities. NIST (the US standards institute) has recently announced standards for public key encryption and signatures which are post-quantum secure. These new standards are based on different mathematical problems, the most prominent of which is a form of noisy linear algebra, called the Learning-with-Errors problem (LWE).

NISTs standards only consider traditional forms of public key encryption and signatures. Fully homomorphic encryption (FHE) is different from traditional public key encryption in that it allows the processing of the data encrypted within the ciphertexts, without the need to decrypt the ciphertexts first.

As a first approximation, one can view traditional public key encryption as enabling efficient encryption of data in transit, whilst FHE offers efficient encryption of data during usage. Most importantly, with FHE nobody would be able to see your data but you because they wouldnt have your key.

All modern FHE encryption schemes are based on the LWE problem, thus FHE is already able to be post-quantum secure. So, if you deploy an FHE system today, then there is no need to worry about the future creation of a quantum computer.

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Surviving the quantum apocalypse with fully homomorphic encryption - Help Net Security

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NVIDIA Amplifies Quantum Computing Ecosystem with New CUDA-Q Integrations and Partnerships at GTC – HPCwire

March 20, 2024 The latest advances in quantum computing include investigating molecules, deploying giant supercomputers and building the quantum workforce with a new academic program. Researchers in Canada and the U.S. used a large language model to simplify quantum simulations that help scientists explore molecules.

This new quantum algorithm opens the avenue to a new way of combining quantum algorithms with machine learning, said Alan Aspuru-Guzik, a professor of chemistry and computer science at the University of Toronto, who led the team.

The effort used CUDA-Q, a hybrid programming model for GPUs, CPUs and the QPUs quantum systems use. The team ran its research on Eos, NVIDIAs H100 GPU supercomputer. Software from the effort will be made available for researchers in fields like healthcare and chemistry. Aspuru-Guzik detailed the work in a talk at GTC.

Quantum Scales for Fraud Detection

At HSBC, one of the worlds largest banks, researchers designed a quantum machine learning application that can detect fraud in digital payments. The banks quantum machine learning algorithm simulated a whopping 165 qubits on NVIDIA GPUs. Research papers typically dont extend beyond 40 of these fundamental calculating units quantum systems use.

HSBC used machine learning techniques implemented with CUDA-Q and cuTensorNet software on NVIDIA GPUs to overcome challenges simulating quantum circuits at scale. Mekena Metcalf, a quantum computing research scientist at HSBC, will present her work in a session at GTC.

Raising a Quantum Generation

In education, NVIDIA is working with nearly two dozen universities to prepare the next generation of computer scientists for the quantum era. The collaboration will design curricula and teaching materials around CUDA-Q.

Bridging the divide between traditional computers and quantum systems is essential to the future of computing, said Theresa Mayer, vice president for research at Carnegie Mellon University. NVIDIA is partnering with institutions of higher education, Carnegie Mellon included, to help students and researchers navigate and excel in this emerging hybrid environment.

To help working developers get hands-on with the latest tools, NVIDIA co-sponsored QHack, a quantum hackathon in February. The winning project, developed by Gopesh Dahale of Qkrishi a quantum company in Gurgaon, India used CUDA-Q to develop an algorithm to simulate a material critical in designing better batteries.

A Trio of New Systems

Two new systems being deployed further expand the ecosystem for hybrid quantum-classical computing.

The largest of the two, ABCI-Q at Japans National Institute of Advanced Industrial Science and Technology, will be one of the largest supercomputers dedicated to research in quantum computing. It will use CUDA-Q on NVIDIA H100 GPUs to advance the nations efforts in the field.

In Denmark, the Novo Nordisk Foundation will lead on the deployment of an NVIDIA DGX SuperPOD, a significant part of which will be dedicated to research in quantum computing in alignment with the countrys national plan to advance the technology.

The new systems join Australias Pawsey Supercomputing Research Centre, which announced in February it will run CUDA-Q on NVIDIA Grace Hopper Superchips at its National Supercomputing and Quantum Computing Innovation Hub.

Partners Drive CUDA-Q Forward

In other news, Israeli startup Classiq released at GTC a new integration with CUDA-Q. Classiqs quantum circuit synthesis lets high-level functional models automatically generate optimized quantum programs, so researchers can get the most out of todays quantum hardware and expand the scale of their work on future algorithms.

Software and service provider QC Ware is integrating its Promethium quantum chemistry package with the just-announced NVIDIA Quantum Cloud.

ORCA Computing, a quantum systems developer headquartered in London, released results running quantum machine learning on its photonics processor with CUDA-Q. In addition, ORCA was selected to build and supply a quantum computing testbed for the UKs National Quantum Computing Centre which will include an NVIDIA GPU cluster using CUDA-Q.

Nvidia and Infleqtion, a quantum technology leader, partnered to bring cutting-edge quantum-enabled solutions to Europes largest cyber-defense exercise with NVIDIA-enabled Superstaq software.

A cloud-based platform for quantum computing, qBraid, is integrating CUDA-Q into its developer environment. And California-based BlueQubit described in a blog how NVIDIAs quantum technology, used in its research and GPU service, provides the fastest and largest quantum emulations possible on GPUs.

Get the Big Picture at GTC

To learn more, watch a session about how NVIDIA is advancing quantum computing and attend an expert panel on the topic, both at NVIDIA GTC, a global AI conference, running March 18-21 at the San Jose Convention Center.

Source: Elica Kyoseva, Nvidia

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