Category Archives: Quantum Computer
Quantum computing just got hotter: 1 degree above absolute zero – The Conversation
For decades, the pursuit of quantum computing has struggled with the need for extremely low temperatures, mere fractions of a degree above absolute zero (0 Kelvin or 273.15C). Thats because the quantum phenomena that grant quantum computers their unique computational abilities can only be harnessed by isolating them from the warmth of the familiar classical world we inhabit.
A single quantum bit or qubit, the equivalent of the binary zero or one bit at the heart of classical computing, requires a large refrigeration apparatus to function. However, in many areas where we expect quantum computers to deliver breakthroughs such as in designing new materials or medicines we will need large numbers of qubits or even whole quantum computers working in parallel.
Quantum computers that can manage errors and self-correct, essential for reliable computations, are anticipated to be gargantuan in scale. Companies like Google, IBM and PsiQuantum are preparing for a future of entire warehouses filled with cooling systems and consuming vast amounts of power to run a single quantum computer.
But if quantum computers could function at even slightly higher temperatures, they could be much easier to operate and much more widely available. In new research published in Nature, our team has shown a certain kind of qubit the spins of individual electrons can operate at temperatures around 1K, far hotter than earlier examples.
Cooling systems become less efficient at lower temperatures. To make it worse, the systems we use today to control the qubits are intertwining messes of wires reminiscent of ENIAC and other huge computers of the 1940s. These systems increase heating and create physical bottlenecks to making qubits work together.
Read more: How long before quantum computers can benefit society? That's Google's US$5 million question
The more qubits we try to cram in, the more difficult the problem becomes. At a certain point the wiring problem becomes insurmountable.
After that, the control systems need to be built into the same chips as the qubits. However, these integrated electronics use even more power and dissipate more heat than the big mess of wires.
Our new research may offer a way forward. We have demonstrated that a particular kind of qubit one made with a quantum dot printed with metal electrodes on silicon, using technology much like that used in existing microchip production can operate at temperatures around 1K.
This is only one degree above absolute zero, so its still extremely cold. However, its significantly warmer than previously thought possible. This breakthrough could condense the sprawling refrigeration infrastructure into a more manageable, single system. It would drastically reduce operational costs and power consumption.
The necessity for such technological advancements isnt merely academic. The stakes are high in fields like drug design, where quantum computing promises to revolutionise how we understand and interact with molecular structures.
The research and development expenses in these industries, running into billions of dollars, underscore the potential cost savings and efficiency gains from more accessible quantum computing technologies.
Hotter qubits offer new possibilities, but they will also introduce new challenges in error correction and control. Higher temperatures may well mean an increase in the rate of measurement errors, which will create further difficulties in keeping the computer functional.
It is still early days in the development of quantum computers. Quantum computers may one day be as ubiquitous as todays silicon chips, but the path to that future will be filled with technical hurdles.
Read more: Explainer: quantum computation and communication technology
Our recent progress in operating qubits at higher temperatures is as a key step towards making the requirements of the system simpler.
It offers hope that quantum computing may break free from the confines of specialised labs into the broader scientific community, industry and commercial data centres.
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Quantum computing just got hotter: 1 degree above absolute zero - The Conversation
Quantum computing progress: Higher temps, better error correction – Ars Technica
There's a strong consensus that tackling most useful problems with a quantum computer will require that the computer be capable of error correction. There is absolutely no consensus, however, about what technology will allow us to achieve that. A large number of companies, including major players like Microsoft, Intel, Amazon, and IBM, have all committed to different technologies to get there, while a collection of startups are exploring an even wider range of potential solutions.
We probably won't have a clearer picture of what's likely to work for a few years. But there's going to be lots of interesting research and development work between now and then, some of which may ultimately represent key milestones in the development of quantum computing. To give you a sense of that work, we're going to look at three papers that were published within the last couple of weeks, each of which tackles a different aspect of quantum computing technology.
Error correction will require connecting multiple hardware qubits to act as a single unit termed a logical qubit. This spreads a single bit of quantum information across multiple hardware qubits, making it more robust. Additional qubits are used to monitor the behavior of the ones holding the data and perform corrections as needed. Some error-correction schemes require over a hundred hardware qubits for each logical qubit, meaning we'd need tens of thousands of hardware qubits before we could do anything practical.
A number of companies have looked at that problem and decided we already know how to create hardware on that scalejust look at any silicon chip. So, if we could etch useful qubits through the same processes we use to make current processors, then scaling wouldn't be an issue. Typically, this has meant fabricating quantum dots on the surface of silicon chips and using these to store single electrons that can hold a qubit in their spin. The rest of the chip holds more traditional circuitry that performs the initiation, control, and readout of the qubit.
This creates a notable problem. Like many other qubit technologies, quantum dots need to be kept below 1 Kelvin in order to keep the environment from interfering with the qubit. And, as anyone who has ever owned an x86-based laptop knows, all the other circuitry on the silicon generates heat. So, there's the very real prospect that trying to control the qubits will raise the temperature to the point that the qubits can't hold onto their state.
That might not be the problem that we thought, according to some work published in Wednesday's Nature. A large international team that includes people from the startup Diraq have shown that a silicon quantum dot processor can work well at the relatively toasty temperature of 1 Kelvin, up from the usual milliKelvin that these processors normally operate at.
The work was done on a two-qubit prototype made with materials that were specifically chosen to improve noise tolerance; the experimental procedure was also optimized to limit errors. The team then performed normal operations starting at 0.1 K and gradually ramped up the temperatures to 1.5 K, checking performance as they did so. They found that a major source of errors, state preparation and measurement (SPAM), didn't change dramatically in this temperature range: "SPAM around 1 K is comparable to that at millikelvin temperatures and remains workable at least until 1.4 K."
The error rates they did see depended on the state they were preparing. One particular state (both spin-up) had a fidelity of over 99 percent, while the rest were less constrained, at somewhere above 95 percent. States had a lifetime of over a millisecond, which qualifies as long-lived in the quantum world.
All of which is pretty good and suggests that the chips can tolerate reasonable operating temperatures, meaning on-chip control circuitry can be used without causing problems. The error rates of the hardware qubits are still well above those that would be needed for error correction to work. However, the researchers suggest that they've identified error processes that can potentially be compensated for. They expect that the ability to do industrial-scale manufacturing will ultimately lead to working hardware.
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Quantum computing progress: Higher temps, better error correction - Ars Technica
3 Quantum Computing Stocks to Buy on the Dip: March 2024 – InvestorPlace
While classical computers have enjoyed tremendous capacity gains over the past few decades, its time for a paradigm shift, which brings the discussion to quantum computing stocks to buy. Here, were not just talking about shifting gears but moving from a race car to a rocket ship.
To be sure, its difficult to explain the various intricacies that help propel quantum computers over their traditional counterparts. But in a nutshell, it comes down to exponentially quicker processing. An attribute called superposition enables quantum computers to evaluate multiple possibilities simultaneously. That makes the new innovation run circles around classical processes.
Further, you cant argue with the numbers. In 2022, the quantum market reached a valuation of $1.9 billion. By 2032, this sector could jump to $42.1 billion, representing a compound annual growth rate of 36.4%.
Who knows? That might end up being a conservative estimate. With so much anticipation, these are the quantum computing stocks to buy for speculators.
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One of the top names in the tech ecosystem, Intel (NASDAQ:INTC) could be one of the underappreciated quantum computing stocks to buy. According to its public profile, designs, develops, manufactures, markets and sells computing and related products and services worldwide. It operates through Client Computing Group, Data Center and AI [artificial intelligence], Network and Edge, Mobileye and Intel Foundry Services segments.
Last year, Intel manufactured a quantum chip, availing it to university and federal research labs to grow the underlying community. While it might not be the most exciting play among quantum computing stocks to buy, its continued research and development makes it a worthy idea to consider.
Financially, the company has performed quite well against expected bottom-line targets. Specifically, Intel mitigated the expected loss per share in the first quarter of 2023 while delivering earnings in Q2 through Q3. Overall, the average positive surprise came out to 177.65% in the past four quarters.
For fiscal 2024, analysts anticipate earnings per share to land at $1.24 on sales of $53.1 billion. Thats a solid improvement over last years 97 cents per share on sales of $50.18 billion.
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Falling under the computer hardware segment of the broader tech ecosystem, IonQ (NASDAQ:IONQ) engages in the development of general-purpose quantum computing systems. Per its corporate profile, the company sells access to quantum computers of various qubit capacities. The company makes access to its quantum computers through cloud platforms. These platforms are offered by enterprises like Amazon (NASDAQ:AMZN), Microsoft (NASDAQ:MSFT) and Alphabet (NASDAQ:GOOGL).
Since the start of the year, IONQ slipped 25%. However, in the past 52 weeks, it has gained 78%. Therefore, those who are willing to tolerate volatility in the near term may benefit from a possible discounted opportunity. On the financials, the company has started to improve its performance.
For example, in Q2 last year, IonQ incurred a negative surprise of 69.2%. In Q3, the metric was 22.2% in the red. However, in Q4, the company met the expected loss per share of 20 cents.
For fiscal 2024, analysts believe that the tech firm could generate revenue of $38.93 million. If so, that would represent a 76.6% increase from last years print of $22 million. Thus, its one of the exciting ideas for quantum computing stocks to buy.
Source: Bartlomiej K. Wroblewski / Shutterstock.com
Another name within the computer hardware subsector, Rigetti Computing (NASDAQ:RGTI), through its subsidiaries builds quantum computers and the superconducting quantum processors. Per its public profile, Rigetti offers cloud services in the form of quantum processing units. It also sells access to its quantum systems via a Cloud Computing as a Service business model.
Now, RGTI generates plenty of attention regarding quantum computing stocks to buy because of its tremendous performance. Since the beginning of the year, Rigetti shares popped up more than 64%. In the trailing 52 weeks, its up almost 175%. However, RGTI is also down 15% in the trailing five sessions, potentially providing speculators with a discount.
Interestingly, Rigetti provides some hits and misses in its quarterly disclosures. In Q2 and Q4, the company beat per-share expectations while missing in Q1 and Q3. For fiscal 2024, Rigetti could generate $16.1 million in revenue. If so, that would be 34.1% higher than last years print of $12.01 million.
Its no wonder, then, that analysts rate RGTI a unanimous strong buy with a $3.25 price target. That implies 115% upside potential.
On the date of publication, Josh Enomoto did not have (either directly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.
A former senior business analyst for Sony Electronics, Josh Enomoto has helped broker major contracts with Fortune Global 500 companies. Over the past several years, he has delivered unique, critical insights for the investment markets, as well as various other industries including legal, construction management, and healthcare. Tweet him at @EnomotoMedia.
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3 Quantum Computing Stocks to Buy on the Dip: March 2024 - InvestorPlace
Revolutionizing Quantum Computing: Breakthroughs in Quantum Error Correction – AZoQuantum
Despite their great potential, quantum computers are delicate devices. Unlike classical computers, qubits (the quantum version of bits) are prone to errors from noise and decoherence. Addressing this challenge, Quantum Error Correction (QEC) is a crucial division of quantum computing development that focuses on resolving qubit errors.
Image Credit:Yurchanka Siarhei/Shutterstock.com
The world of atoms and subatomic particles is governed by the laws of quantum mechanics. Quantum computing harnesses these principles, performing calculations in a completely different way from traditional computers.
Regular computers use bits, which can be either 0 or 1. Quantum computers, however, exploit the bizarre property of superposition, allowing qubits to be 0, 1, or both at the same time. The ability to be in multiple states simultaneously enhances the processing power of quantum computers.
Qubits are made from quantum particles like electrons or photons. By controlling properties like electrical charge or spin, data can be represented as 0, 1, or a combination of both. To unlock the true power of quantum computers, scientists rely on two unique properties:
There is no preferred qubit technology; instead, a range of physical systems, such as photons, trapped ions, superconducting circuits, and semiconductor spins, are being investigated for use as qubits.1
All these methods face the common challenge of isolating qubits from external noise, making errors during quantum computation inevitable. In contrast, classical computer bits, realized by the on/off states of transistor switches with billions of electrons, have substantial error margins that virtually eliminate physical defects.
There is no equivalent error-prevention security for quantum computers, where qubits are realized as fragile physical systems. Thus, active error correction is necessary for any quantum computer relying on qubit technology.
In 1995, Peter Shor introduced the first quantum error-correcting method. Shors approach demonstrated how quantum information could be redundantly encoded by entangling it across a larger system of qubits.
Subsequent findings then showed that if specific physical requirements on the qubits themselves are satisfied, extensions to this technique may theoretically be utilized to arbitrarily lower the quantum error rate.
While diverse efforts are being undertaken in the field of QEC, the fundamental approach to QEC implementation involves the following steps.
Quantum information is encoded across several physical, distributed qubits. These qubits act as 'information holders' for a 'logical qubit,' which is more robust and contains the data used for computation.
The logical qubits are then entangled with the physical information holders using a specific QEC code. These additional physical qubits serve as sentinels for the logical qubit.
QEC identifies errors in the encoded data by measuring the information holders using a method that does not affect the data directly in the logical qubit. This measurement provides an indication or a pattern of results that shows the type and location of the error.
Different QEC codes are available for the various types of errors that could occur. Based on the detected error, the chosen QEC system applies an operation to correct the error in the data qubits.
Error correction itself has the potential to generate noise. Therefore, additional physical qubits are required to maintain the delicate balance of correcting errors and limiting the introduction of new ones.
To realize the full potential of a quantum computer, the number of logical qubits has to be increased. However, since each logical qubit requires several physical qubits for error correction, the complexity and resources needed to isolate and manage high-quality qubits become considerable obstacles to scalability.
In recent years, quantum error correction has seen significant advancements, and the community's focus has shifted from noisy applications to the potential uses of early error-corrected quantum computers. Though research on superconducting circuits, reconfigurable atom arrays, and trapped ions has made significant strides, several platform-specific technological obstacles remain to be solved.
Some notable recent advancements in QEC include:
Despite the challenges, QEC is essential for building large-scale, fault-tolerant quantum computers. Researchers are constantly developing new and improved QEC codes and techniques.
As quantum technology progresses, QEC will play a critical role in unlocking the true potential of this revolutionary field.
More from AZoQuantum: Harnessing Quantum Computing for Breakthroughs in Artificial Intelligence
Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.
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Revolutionizing Quantum Computing: Breakthroughs in Quantum Error Correction - AZoQuantum
First Business PCs to Protect Firmware Against Quantum Computer Hacks – Manufacturing.net
The potential introduction of quantum computerscapable of breaking asymmetric cryptography could place the entire digital world at risk, and this risk is becoming increasingly plausible every day.This led HP tounveilPCs designed to protect firmware against quantum computer attacks. Features include:
Research showsthat 27 percent of experts think there is a 50 percent likelihood of a cryptographically relevant quantum computer (CRQC) by 2033. When that day comes, thesecurity of existing digital signatures on firmware and software will be in question. (Read more on Anticipating the Quantum threat to Cryptographyhere).
Migrating the entire digital world to a new cryptographic standard is a huge undertaking, and while software can be updated, hardware cant. That includes some of the cryptography that protects PC firmware. With no cryptographic protections in place, no device would be safe attackers could access and modify the underlying firmware and gain total control.
HP also recommends that customers start to assess how and when to start migrating all other aspects of their information systems to quantum-resistant cryptography. This includes three steps to begin planning:
For further information on our fifth generation ESC chipavailability, click here.
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First Business PCs to Protect Firmware Against Quantum Computer Hacks - Manufacturing.net
Alice & Bob and partners awarded 16.5M to slash quantum computing costs – Tech.eu
Quantum computing hardware developer Alice & Bob and academic partners ENS de Lyon and Mines Paris-PSL today announced the receipt of a 16.5 million innovation grant, a France 2030 initiative operated by Bpifrance, France's public investment bank.
Alice & Bob is based in Paris and Boston and is working to create the first universal, fault-tolerant quantum computer. Founded in 2020, the company has raised 30 million in funding, hired over 95 employees and demonstrated experimental results surpassing those of technology giants such as Google or IBM.
Alice & Bob specialises in cat qubits, a pioneering technology developed by the company's founders and later adopted by Amazon.
The funded project, called "Cat Factory," brings industry and government partners to tackle quantum computing's critical issues across various enabling technologies, including nanofabrication, chip design and validation, digital tools and electronic control.
The research from the three partners aims to accelerate quantum computing by enhancing the efficiency of the entire stack, reducing costs, and accelerating market readiness.
The goal is to develop a new optimised architecture for fault-tolerant quantum computing by 2027 that will allow the following:
Reduction of the number of control lines per cat qubit from 4.5 to 2 Reduction of the readout lines per cat qubit from 1 to 0.2
To achieve this degree of optimisation, the infrastructure of enabling technologies surrounding the Quantum Processing Unit (QPU) will be updated to: Increase the number of analogue ports per rack from 60 to 180, dividing the footprint of control electronics by three. Increase control lines per cryostat from 200 to 2000 using next-generation cabling technology.
According to Theau Peronnin, CEO of Alice & Bob:
"We are honoured to be entrusted with making quantum computing useful earlier. Our plan, centred around cat qubits, addresses the real challenges of quantum computing headfirst, enabling massive savings in energy and end-user costs."
The projected cost of quantum computation due to cryogenics and the control of large sets of qubits presents a barrier to widespread adoption. Alice and Bob will use the funding to optimise quantum computation, from design to manufacturing and infrastructure, to make quantum computers ten times cheaper to build and ready for market three years earlier.
"Quantum computing algorithms require hundreds of logical qubits, which translates to thousands to millions of physical qubits," said Florent Di Meglio, the project's lead at Mines ParisPSL.
"Cat Factory aims to reach 100 logical qubits with only three cryostats, a dramatic reduction in the hardware needed for running a useful quantum computer."
To achieve this goal, the partners will work on the whole quantum computer architecture and the infrastructure of enabling technologies surrounding it. The project's cornerstone, the cat qubit, already reduces the number of physical qubits required to build a logical one by a factor of 60.
Paul-Franois Fournier, Executive Director, ofInnovation at Bpifrance, shared:
"We are delighted to support Alice & Bob in its development, which aims to accelerate quantum computing's progress. This support reflects Bpifrance's strong ambitions in terms of disruptive innovation."
Lead image: Alice & Bob.
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Alice & Bob and partners awarded 16.5M to slash quantum computing costs - Tech.eu
3 Quantum Computing Stocks to Buy for the Next Bull Run: March 2024 – InvestorPlace
There are some quantum computing stocks to buy for March that I think could lift off to new heights.
Quantum computing is an emerging and potentially revolutionary technology that could have a profound impact on various industries and fields. The market potential for quantum computing is immense. It is widely regarded as one of the most promising technological advancements of the 21st century.
The great thing about these companies is that many of them are speculative investments and therefore trade at attractive valuations. I think that these companies are primed for the next bull run. As the Nasdaq moves higher, so too will these options.
So, here are three quantum computing stocks for investors to consider for March this year.
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IonQ (NYSE:IONQ) distinguishes itself as a pure-play quantum computing company. They have a strong focus on developing trapped ion quantum computers.
For this year, it projects its revenue for the full year 2024 to range between $37 million and $41 million. Its bookings are expected to be between $70 million and $90 million. For the first quarter of 2024, revenue is forecasted to be between $6.5 million and $7.5 million. Despite these projections, IONQ anticipates an adjusted EBITDA loss of $110.5 million for 2024.
The companys performance in 2023 set a strong foundation for these forecasts. They had significant achievements including hitting $65.1 million in bookings for the year, exceeding the upper end of its guidance. This represents a 166% growth compared to the previous year. The revenue for 2023 was reported at $22.042 million, a substantial increase from $11.131 million in 2022
I see the projected loss as potentially being a good thing for IONQ investors. This could keep its valuation down to acceptable levels. Due to its small market cap of 1.9 billion, it could rise significantly along with the broader market amid a bull run.
Source: Bartlomiej K. Wroblewski / Shutterstock.com
Rigetti Computing (NASDAQ:RGTI) is known for developing quantum integrated circuits. They also offer a cloud platform that supports quantum algorithm development.
In my opinion, RGTI is one of the more underestimated companies in this list. This is because it has an angle of offering more of the picks and shovels to the quantum industry rather than being a pure-play option than IONQ. Investing in RGTI could then give one more indirect than direct exposure to the industry. This could be a strong diversifier.
In terms of outlook and developments, RGTI made significant progress in 2023, including the deployment of the 84-qubit Ankaa-2 quantum computer, which achieved a 98% median 2-qubit fidelity and a 2.5x improvement in error performance compared to its previous quantum processing units (QPUs).
Underscoring why I believe that it could be a strong contender, analysts have given RGTI a Moderate Buy rating, with a consensus price target of $2.75, indicating a potential upside of 71.34% to be reached within the next twelve months.
Source: JHVEPhoto / Shutterstock.com
IBM (NYSE:IBM) extends its influence in quantum computing beyond hardware.
I chose IBM for investors who want a well-diversified blue-chip investment rather than the more speculative companies on this list. Although its potential for capital growth may be lower, I feel that with its dividend yield of 3.52% at the time of writing, this makes it a solid and safer choice.
IBM is also expanding its global footprint in quantum computing with the establishment of its first European quantum data center in Germany, set to open in 2024. This facility will enable users in Europe to access IBMs quantum computing systems and services.
Hardware-wise, IBM has introduced advanced processors like the 133-qubit Heron and the 433-qubit Osprey. Meanwhile, On the software front, IBM is evolving its Qiskit platform with updates that promise to increase the ease of quantum software programming.
IBM then has many forks in the fire to take advantage of the rise of quantum computing, which along with its stability and dividend yield, makes it one of those stocks that could rise in a bull run. If you are looking for quantum computing stocks to buy, you cant go wrong with these.
On the date of publication, Matthew Farley did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.
Matthew started writing coverage of the financial markets during the crypto boom of 2017 and was also a team member of several fintech startups. He then started writing about Australian and U.S. equities for various publications. His work has appeared in MarketBeat, FXStreet, Cryptoslate, Seeking Alpha, and the New Scientist magazine, among others.
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3 Quantum Computing Stocks to Buy for the Next Bull Run: March 2024 - InvestorPlace
UNI’s Begeman Lecture to explore how quantum computing is revolutionizing our world – Cedar Valley Daily Times
Quantum computing, and how its revolutionizing our world, is the focus of this years Begeman Lecture in Physics at the University of Northern Iowa.
The lecture, titled Building a Quantum Computer, One Atom at a Time, will be presented by UNI Department of Physics alum Justin Bohnet on Wednesday, April 3 at 7 p.m. in the Lang Hall Auditorium. The event is free and open to the public.
Justin is in the vanguard of efforts to develop quantum computers for widespread use, said Paul Shand, head of the UNI Department of Physics. Were excited for him to share more about quantum computers and how they will turbocharge computing in the future.
Bohnet is the research & development manager at Quantinuum a quantum computing company whose mission is to accelerate quantum computing and use its power to achieve unprecedented breakthroughs in drug discovery, health care, materials science, cybersecurity, energy transformation and climate change.
In this lecture, Bohnet will share his personal journey from a student at UNI to building the worlds most powerful quantum computers, powered by control over single atoms. Along the way, youll get a crash course on quantum computers what they are, how they work and why were standing on the brink of a technological revolution that will let us explore uncharted territories of science and technology.
If you need a reasonable accommodation in order to participate in this event, please contact the UNI Department of Physics by calling 319-273-2420 or by emailing physics@uni.edu prior to the event.
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UNI's Begeman Lecture to explore how quantum computing is revolutionizing our world - Cedar Valley Daily Times
Exploring the potential of quantum reservoir computing in forecasting the intensity of tropical cyclones – Moody’s Analytics
What is the problem?
Accurately predicting the intensity of tropical cyclones, defined as the maximum sustained windspeed over a period of time, is a critical yet challenging task. Rapid intensification (RI) events are still a daunting problem for operational intensity forecasting.
Better forecasts and simulation of tropical cyclone (TC) intensities and their track can significantly improve the quality of Moodys RMS tropical cyclone modeling suite. RMS has helped clients manage their risk during TC events in the North Atlantic for almost 20 years. Real time TCs can significantly impact a companys financial, operational, and overall solvency state. Moodys RMS Hwind product helps (re)insurers, brokers, and capital markets understand the range of potential losses across multiple forecast scenarios, capturing the uncertainty in of how track and intensity will evolve.
With the advances in Numerical Weather Prediction (NWP) and new meteorological observations, forecasts of TC movement have progressively improved in global and regional models. However, the model accuracy in forecasting the intensities of TCs remains challenging for operational weather forecasting and consequential assessment of weather impacts such as high winds, storm surges, and heavy rainfall.
Since the current spatial resolution of the NWP model is insufficient for resolving convective scale processes and inner core dynamics of the cyclone, forecast intensities of TCs from operational models are mostly underestimated or low biased. Yet, accurate TC intensity guidance is crucial not only for assessing the impact of the TC, but also for generating realistic projections of storms and their associated hazards. This is essential for effective risk evaluation. Conventional TC intensity forecasting mainly relies on three approaches: statistical, dynamical, and statistical-dynamical methods.
Dynamical models, also known as numerical models, are the most complex and use high performance computing (HPC) to solve the physical equations of motion governing the atmosphere. While statistical models do not explicitly consider the physics of the atmosphere, they are based on historical relationships between storm behavior and storm-specific details such as location and intensity.
The rise of Machine Learning (ML) and Deep Learning (DL) has led to attempts to create breakthroughs in climate modeling and weather forecasting. Recent advances in computational capabilities and the availability of extensive reanalysis of observational or numerical datasets have reignited interest in developing various ML methods for predicting and understanding the dynamics of complex systems.
One of our key objectives is to build a quantum reservoir computing-based model, capable of processing climate model outputs and storm environment parameters, to provide more accurate forecasting, will improve short-term and real-time TC risk analysis.
Official modeling centers use consensus or ensemble-based dynamical models and represent the state of the art in tropical cyclone forecasting. However, these physics-based models may be subject to bias derived from high wind shear, low sea surface temperatures, or the storms location in the basin. By learning from past forecasting errors, we may be able to identify and correct past model biases, thereby greatly enhancing the quality of future forecasting and risk modeling products. The long-term aim is to integrate ML-based elements into coarse global climate models to improve their resolution and include natural dynamical processes currently absent in these models.
Reservoir Computing (RC) is a novel machine-learning algorithm particularly suited to quantum computers and has shown promising results in early non-linear time series prediction tests. In a classical setting, RC is stable and computationally simple. It works by mapping input time series signals into a higher dimensional computational space through the dynamics of a fixed, non-linear system known as a reservoir. This method is efficient, trainable, and has a low computational cost, making it a valuable tool for large-scale climate modeling.
While quantum machine learning has been considered a promising application for near-term quantum computers, current quantum machine learning methods require large quantum resources and suffer from gradient vanishing issues. Quantum Reservoir Computing (QRC) has the potential to combine the efficient machine learning of classical RC with the computing power of complex and high-dimensional quantum dynamics. QRC takes RC a step further by leveraging the unique capabilities of quantum processing units (QPUs) and their exponentially large state space, resulting in rich dynamics that cannot be simulated on a conventional computer. In particular, the flexible atom arrangements and tunability of optical controls within QuEras neutral atom QPU enable the realization of a rich class of Hamiltonians acting as the reservoir.
Recent studies on quantum computing simulators and hardware suggest that certain quantum model architectures used for learning on classical data can achieve results similar to that of classical machine learning models while using significantly fewer parameters. Overall, QRC offers a promising approach to resource-efficient, noise-resilient, and scalable quantum machine learning.
In this project, we are collaborating with QuEra Computing, the leading provider of quantum computers based on neutral-atoms , to explore the benefits of using quantum reservoir computing in climate science and to investigate the potential advantages that the quantum layer from QuEra can bring. QuEra's neutral atom QPU and the types of quantum simulations it can perform give rise to different quantum reservoirs. This unique capability can potentially enhance the modeling of tropical cyclone intensity forecasts and data.
This collaboration involves multiple stakeholders and partners, including QuEra Computing Inc., Moodys RMS technical team, and Moodys Quantum Taskforce. The work is supported by a DARPA grant award, underscoring its significance and potential impact in tropical cyclone modeling and forecasting.
In summary, combining quantum machine learning methods, reservoir computing, and the quantum capabilities of QuEra's technology offers a promising approach to addressing the challenges in predicting tropical cyclone intensity. This collaboration aims to enhance the quality and efficiency of tropical cyclone modeling, ultimately aiding in better risk assessment and decision making in the face of these natural disasters.
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Exploring the potential of quantum reservoir computing in forecasting the intensity of tropical cyclones - Moody's Analytics
Quantum startup Alice & Bob receives innovation grant to make quantum computing cheaper – DatacenterDynamics
Quantum startup Alice & Bob has received a 16.5 million ($17.8 million) innovation grant from Frances public investment bank, Bpifrance.
The French startup is the first company to receive all four innovation grants from Bpifrance and the funds will be used to finance a 36-month project that will see the company enhance the efficiency of its quantum stack, reducing manufacturing costs and time to market.
The deal has been endorsed by the office of Prime Minister Gabriel Attal.
Dubbed Cat Factory after cat qubit technology, the project will bring together industry, government, and academic partners from ENS de Lyon and Mines Paris (PSL) to address a number of critical issues related to quantum computing, including nanofabrication, chip design and validation, digital tools, and electronic control.
The team is aiming to develop a new optimized architecture for fault-tolerant quantum computing by 2027 that will allow a reduction in the number of control lines per cat qubit from 4.5 to 2, and a reduction in the readout lines per cat qubit from 1 to 0.2.
In order to achieve this, the Quantum Processing Unit (QPU) architecture will be updated to increase the number of analog ports from 60 to 18 per rack, and increase the number of control lines per cryostat from 200 to 2000.
Quantum computing algorithms require hundreds of logical qubits, which translates to thousands to millions of physical qubits, said Florent Di Meglio lead on the project at Mines Paris, PSL. Cat Factory aims to reach 100 logical qubits with only 3 cryostats, a dramatic reduction in the hardware needs for running a useful quantum computer.
Theau Peronnin, CEO of Alice & Bob, added: We are honored to be entrusted with the task of making quantum computing useful earlier. Our plan, centered around cat qubits, addresses the real challenges of quantum computing headfirst, enabling massive savings in energy and end-user costs.
Founded in 2020, Alice & Bob has already raised 30 million across six funding rounds to develop a fault-tolerant quantum processor.
Earlier this month, the company was given access to 500 million in funding after being invited by the French Ministry for Armed Forces to participate in the countrys PROQCIMA initiative.
Those project participants will work to deliver a universal fault-tolerant quantum computer demonstrator with 128 logical qubits by 2030, and its industrialization into a 2048-logical-qubits computer by 2035.
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Quantum startup Alice & Bob receives innovation grant to make quantum computing cheaper - DatacenterDynamics