Category Archives: Quantum Computing
Quantum computing breakthrough: a phase of matter that exists in two time dimensions – Interesting Engineering
Scientists with funding from the Simons Foundation produced a phase of matter that behaves as if it exists in two time dimensions, according to a press release by the institution published on Wednesday. The researchers created the strange material byshining a sequence of laser pulses inspired by the Fibonacci numbers at atoms inside a quantum computer.
Information stored in the strange new phase of matter is far more protected against errors than information stored with the conventional setups currently used in quantum computers. The data can survive for much longer before becoming garbled, potentially makingquantum computing viable, said study lead author Philipp Dumitrescu.
The use of a novel extra time dimension is a completely different way of thinking about phases of matter, said Dumitrescu, who worked on the project as a research fellow at the Flatiron Institutes Center for Computational Quantum Physics in New York City. Ive been working on these theory ideas for over five years, and seeing them come actually to be realized in experiments is exciting.
Quantum computers use elements called qubits to store and handle information, but there's a problem with that. Interacting with these qubits messes with their states leading to problems and errors.
"Even if you keep all the atoms under tight control, they can lose their quantumness by talking to their environment, heating up or interacting with things in ways you didnt plan, Dumitrescu said. In practice, experimental devices have many sources of error that can degrade coherence after just a few laser pulses.
The scientists were therefore looking for ways to make these qubits more robust.To achieve that, physicists can use properties that hold up to change such assymmetries."
Dumitrescu and his team usedthe creation of a quasicrystal in time rather than space and proceeded to develop a quasi-periodic laser-pulse regimen based on the Fibonacci sequence.
"In such a sequence, each part of the sequence is the sum of the two previous parts (A, AB, ABA, ABAAB, ABAABABA, etc.). This arrangement, just like a quasicrystal, is ordered without repeating. And, akin to a quasicrystal, its a 2D pattern squashed into a single dimension. That dimensional flattening theoretically results in two time symmetries instead of just one: The system essentially gets a bonus symmetry from a nonexistent extra time dimension," explained the institution's statement.
Further tests undertaken by the physicists demonstrated that the new phase of matter can act as long-term quantum information storage. However, the researchers still need to functionally integrate the phase with the computational side of quantum computing.
Thats an open problem were working on," saidDumitrescu. Should they come up with a solution it could forever change how we approach quantum computing.
Quantum computer works with more than zero and one – EurekAlert
image:The Innsbruck quantum computer stores information in individual trapped calcium atoms, each of which has eight states, of which the scientists have used up to seven for computing. view more
Credit: Uni Innsbruck/Harald Ritsch
We all learn from early on that computers work with zeros and ones, also known as binary information. This approach has been so successful that computers now power everything from coffee machines to self-driving cars and it is hard to imagine a life without them.
Building on this success, todays quantum computers are also designed with binary information processing in mind. The building blocks of quantum computers, however, are more than just zeros and ones, explains Martin Ringbauer, an experimental physicist from Innsbruck, Austria. Restricting them to binary systems prevents these devices from living up to their true potential.
The team led by Thomas Monz at the Department of Experimental Physics at the University of Innsbruck, now succeeded in developing a quantum computer that can perform arbitrary calculations with so-called quantum digits (qudits), thereby unlocking more computational power with fewer quantum particles.
Although storing information in zeros and ones is not the most efficient way of doing calculations, it is the simplest way. Simple often also means reliable and robust to errors and so binary information has become the unchallenged standard for classical computers.
In the quantum world, the situation is quite different. In the Innsbruck quantum computer, for example, information is stored in individual trapped Calcium atoms. Each of these atoms naturally has eight different states, of which typically only two are used to store information. Indeed, almost all existing quantum computers have access to more quantum states than they use for computation.
The physicists from Innsbruck now developed a quantum computer that can make use of the full potential of these atoms, by computing with qudits. Contrary to the classical case, using more states does not make the computer less reliable. Quantum systems naturally have more than just two states and we showed that we can control them all equally well, says Thomas Monz.
On the flipside, many of the tasks that need quantum computers, such as problems in physics, chemistry, or material science, are also naturally expressed in the qudit language. Rewriting them for qubits can often make them too complicated for todays quantum computers. Working with more than zeros and ones is very natural, not only for the quantum computer but also for its applications, allowing us to unlock the true potential of quantum systems, explains Martin Ringbauer.
Publikation: A universal qudit quantum processor with trapped ions. Martin Ringbauer, Michael Meth, Lukas Postler, Roman Stricker, Rainer Blatt, Philipp Schindler, Thomas Monz. Nature Physics 2022. DOI:10.1038/s41567-022-01658-0 [arXiv:2109.06903]
Experimental study
A universal qudit quantum processor with trapped ions
21-Jul-2022
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Quantum computer works with more than zero and one - EurekAlert
BASF looks to quantum computing to improve weather modeling – The Register
A new quantum computing partnership could pave the way to more efficient climate change modeling.
BASF and French quantum computing startup Pasqal have linked arms in a move that will see the chemical giant use Pasqal's proprietary quantum tech to improve its ability to predict the weather.
BASF's chemicals are found in a variety of products and materials. One of its sectors involves a portfolio of farming optimization software that includes xarvio Field Manager, a crop optimization platform. BASF uses weather models to inform its software's crop growth simulations, pesticide drift and other metrics, and believes Pasqal's quantum systems could help.
Physics-based weather modeling is complicated. Wind data, heat transfer, solar radiation, humidity, topology, and other factors combine into complex nonlinear differential equations that need solving, Pasqal said.
"Pasqal aims to solve the [math] in a novel and more efficient way by implementing so-called quantum neural networks on its neutral atom quantum processors," the company said.
There's already a non-quantum model that does what Pasqal and BASF are aiming toward: Nvidia's Earth-2 supercomputer. As opposed to using quantum algorithms, Nvidia's climate prediction model relies on physics-informed neural networks, which are commonly used for weather and climate modeling.
Dr John Manobianco, senior weather modeler at BASF's agricultural solutions division, said BASF's work with Pasqal would help it simplify computational simulations "once quantum hardware matures to a point where we can actually leverage these algorithms."
Pasqal said the information it learns from the collaboration with BASF can "build a foundation for future extensions of Pasqal's methods to support climate modeling."
Benno Broer, chief commercial officer at Pasqal, told The Register that Pasqal's work with BASF will "parameterize, implement and test Pasqal's proprietary family of quantum algorithms for solving differential equations."
Pasqal's differential equation solving algorithm has also been used by BMW to reduce vehicle component testing time. Along with its partnerships with BASF and BMW, Pasqal also announced an agreement with Saudi Aramco in March, and claims Johnson & Johnson, LG, Airbus as other customers.
With BASF, Pascal's differentiable quantum circuit (DQC) algorithm will be turned to predicting weather patterns, which Broer said will lead to Pasqal being able to specialize its algorithm.
"We expect to be able to tailor [DQC algorithms] to model such patterns on multiple spatial and temporal scales, meaning both long-term and short-term, local and global patterns (including climate change patterns) and events," Broer said.
With recent climate events bad enough to knock Google and Oracle data centers offline in Britian and do lasting damage, faster and longer-term weather modeling is definitely needed.
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BASF looks to quantum computing to improve weather modeling - The Register
Quantum: Claims Solving 3,854-Variable Optimization Problem in 6 Minutes for BMW – High-Performance Computing News Analysis | insideHPC – insideHPC
LEESBURG, Va., July 20, 2021 Quantum Computing Inc. (QCI) today announced it has solved an optimization problem with over 3,800 variables in six minutes by applying a new quantum hardware technology called Entropy Quantum Computing (EQC) to the BMW Vehicle Sensor Placement challenge. The problem consisted of 3,854 variables and more than 500 constraints. In comparison, todays Noisy Intermediate Scale Quantum (NISQ) computers can process approximately 127 variables for a problem of similar complexity.
The 2021BMW GroupandAmazon Web Services (AWS)Quantum Computing Challenge included a Vehicle Sensor Placement use case that challenged participants to find optimal configurations of sensors for a given vehicle that would provide maximum coverage (i.e. detect obstacles in different driving scenarios) at minimum cost. Although QCI placed as a 2021 finalist, its 2022 acquisition of quantum photonics systems company QPhoton provided a powerful suite of new quantum hardware technologies, including EQC. As a result, QCI today presented BMW with a 2022 solution: a superior sensor configuration consisting of 15 sensors yielding 96% coverage using QCIs quantum hardware and software.
The EQC ran over 70x faster than QCIs 2021 hybrid DWave implementation. While the speed itself is notable, the stability of the system allowed the Company to run the problem repeatedly and iteratively, demonstrating its usefulness for business applications.
We are very proud to have achieved what we believe to be an important landmark result in the evolution of quantum, said Bob Liscouski, CEO of QCI. We believe that this proves that innovative quantum computing technologies can solve real business problemstoday. Whats even more significant is the complexity of the problem solved. This wasnt just a rudimentary problem to show that quantum solutions will be feasible someday; this was a very real and significant problem whose solution can potentially contribute to accelerating the realization of the autonomous vehicle industry today.
Historically, commercially-available QPU architectures have only been able to process problems with minimal variable sizes, due to the limited number of qubits available to represent problem variables. These systems also sometimes suffer from significant errors in processing as well as stability and calibration issues, further limiting their commercial viability in todays market. In contrast, QCIs EQC can process computations over a many-variable space, with coherence, thus providing powerful quantum solutions to real-world problems.
EQC operates on the most fundamental principles of quantum physics, especially its measurement postulate, wherein the wave function of a quantum system will collapse to a certain eigenstate due to its interaction with a measurement apparatus or, broadly speaking, the surrounding environment. However, while existing quantum computing architectures must operate on closed quantum systems under extreme requirements to calm the effects of the environment, EQC operates on open quantum systems, carefully coupling a quantum system to an engineered environment, so that its quantum state is collapsed to represent a problemsdesirable solution.
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Quantum: Claims Solving 3,854-Variable Optimization Problem in 6 Minutes for BMW - High-Performance Computing News Analysis | insideHPC - insideHPC
Pasqal, BASF aim to improve weather modeling with quantum computing – VentureBeat
Paris-based Pasqal, a full-stack neutral atom quantum computing provider, and BASF, the multinational chemical juggernaut, are announcing a partnership focused on weather modeling and other computational fluid-dynamics applications. That area of problem-solving relies on solving complex nonlinear differential equations, a task for which, it turns out, Pasqals hardware and algorithms are especially well-suited.
VentureBeat spoke with Benno Broer, Pasqals chief commercial officer. Broer was CEO of Qu & Co. which was focused on quantum algorithms and software, and which merged with Pasqal in January of this year.
Broer said that Pasqals hardware platform implements qubits (quantum bits), using individually trapped atoms that are manipulated with laser beams, and that the company produces 100-qubit systems today. The neutral atom platform supports an analog mode, which enables addressing all of those qubits concurrently, thereby enabling quantum entanglement, where multiple qubits act as a single system and influence each other.
Building on this, Pasqals algorithm technology can implement quantum neural networks, the quantum computing equivalent of physics-informed neural networks (PINNs), a subset of physics-informed machine learning (PIML). In the PIML world, models can be trained using a combination of data and equations that describe the laws of physics underlying the modeled phenomena.
PIML techniques can be used to solve differential equations, which is the key to attacking computational fluid-dynamics applications, including weather modeling. According to Pasqals press release, BASF can then use parameters generated by the weather models to simulate crop yields and growth stages as well as to predict drift when applying crop protection products. The weather modeling further serves BASFs digital farming product portfolio, including an advanced crop optimization platform. This takes quantum computing down from the ivory tower, and applies it, quite literally, in the field.
Perhaps even more intriguing, Broer told VentureBeat the equations used to model short-term weather patterns and those for long-term climate modeling are, in fact, similar. Scaling up the time dimension can allow the technology being applied to weather modeling in the near future to be applicable to climate modeling later, and perhaps be used to mitigate the effects of climate change.
Given the heatwaves impacting so many regions across the world this week, the potential of quantum computing to help mitigate climate change impact is good news . And if were going to tech our way out of this (the phrase attributed to Kleiner Perkins chairman John Doerr), then an approach that combines quantum computing and physics-informed machine learning seems like a good start.
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Pasqal, BASF aim to improve weather modeling with quantum computing - VentureBeat
Quantum computing and its impact on cybersecurity [Q&A] – BetaNews
Quantum computing with its vastly improved processing capability offers the chance of many positive developments in research and science. But it also represents a potential threat to our current encryption models.
How big is quantum's threat to cybersecurity? And should we be taking action on this now? We talked to Skip Sanzeri, QuSecure co-founder and COO, to find out.
BN: What are some of the main trends around quantum computing development?
SS: The quantum computing industry is evolving rapidly. Just a few years ago we were struggling to find companies that had more than a few dozen qubits and now we are in the 100-qubit era. Companies such as IBM, IonQ, Google, and PsiQuantum are talking about having a thousand or more qubits by mid-decade. If coherence continues to advance and noise can be reduced, these systems will be even more powerful. The promise of quantum computing, due to the exponential nature of qubits in superposition, can do amazing things for society -- but job one is cybersecurity.
With the advent of quantum computing upon us, the potential for many positive enhancements to our society may be forthcoming, including algorithms to cut through global emissions and quantum chemistry for personalized medicine. At the same time, tens of billions of dollars are being spent by foreign nations to develop quantum computers (some of which have been openly declared as 'weaponized'). A quantum computer with approximately 4,000 qubits will be able to break RSA 2048 which is the primary algorithm that we rely on to keep the world's data safe on the internet. So, we should prepare for the possibility that the first use of quantum computing may be for harm rather than good.
BN: Why is the need for action now when we know quantum computers are years away?
SS: Store now, decrypt later attacks are the biggest reason to start upgrading networks and communications to post-quantum cybersecurity (PQC). Foreign nation states are stealing data every second of the day. This data is harvested and stored on computers waiting to be decrypted. Quantum computers will be able to crack encryption (proven mathematically by Shores Algorithm) once we reach the scale of around 4,000 qubits. We refer to this as 'Q-Day.' So, all data that is encrypted with current, non-PQC is at risk today of a quantum computer decrypting it in the future. For example, if a quantum computer with enough power to crack encryption is developed in five years, data stolen today would still be very valuable if it has 10, 20, or more years of shelf life. National security secrets, bank account information, and electronic health records may have data security requirements of up to 75 years. Making matters worse, many experts estimate that changing our current encryption across an enterprise or government agency could take as long as 10 years. Adding this to the shelf life of data means that there are 10 more years of exposed data which attackers can weaponize or use against us. In many cases, we are already behind.
Therefore, enterprises (and government already has mandates in place) should start looking very closely at PQC to encrypt current communications and data. If data is stolen but has quantum encryption, it will be safe for decades after Q-Day.
BN: What are the main challenges around addressing the post-quantum cyber threat?
SS: There are a variety of challenges to overcome when thinking about how organizations can become quantum resilient.
First, any change is difficult. Moving from older, legacy systems to newer technologies takes a great deal of planning, time and resources in order to not disrupt operations. Therefore, any upgrades, especially to cybersecurity, need to be backwards compatible so that the upgrade process can move more efficiently.
Second, cutting-edge technology always comes with risk. Betting on new technologies requires significant risk assessment to ensure that upgrades are carefully planned, and best-of-breed vendors are chosen. Using standards-based technologies such as the algorithms that NIST is recommending will help reduce risk. Also looking for companies that have referenceable clients, federally approved credentials, post-quantum cybersecurity, and successful implementations will reduce risk.
BN: What are some of the things organizations should look for in a PQC solution to best protect their data?
SS: Enterprises and government agencies need to look for solutions that are standards-based, backwards compatible, and have cryptographic agility. Using NIST algorithms helps satisfy standards risk. Selecting vendors that can transfer between existing systems and protocols to newer post-quantum protocols is vital so that companies dont have to rip and replace software, which causes disruption and risk. Cryptographic agility means that implementations can use a variety of cryptographic standards such as any of the NIST finalists, which further means that an organization can choose its cryptography versus being locked into just one type of cryptography due to a given vendors choice. By finding a partner like QuSecure that has an adaptive orchestrated solution with continuous availability that standardizes on all the NIST finalists, an organization can know that they have optimized their choice.
BN: There seem to be multiple options in terms of PQC solutions, which are the most optimal and why?
SS: A variety of vendors are coming on scene to help meet this massive upgrade need. There are some solutions that focus on Quantum Key Distribution (QKD). QKD is the idea that you can use two devices to transmit keys via entanglement making the transmission theoretically un-spyable, but it is currently severely range-limited. It is currently only useful for highly specific applications and requires significant scientific breakthroughs to make it applicable to larger networks. Some vendors offer quantum random number generation (ORNG), which serves generally random numbers for use in cryptographic keys. This solves the threat of pseudo random keys (programmatically generated random numbers, which is the standard today) being reverse engineered, but QRNG alone does not address the threat posed to public key cryptography by Shors Algorithm attacks.
Other vendors have teams of mathematicians that offer post quantum cryptographic algorithms, and these fall into two camps. The first is a class of proprietary cryptographic algorithms, and it is generally not recommended to implement non-standard algorithms in an enterprise or government environment. The second class is a handful of companies that have written NIST finalist algorithms and offer generally application specific implementations. Still other vendors offer consulting services for PQC implementation.
Optimally an organization should find the right mix of post-quantum cybersecurity software, hardware and services, and ideally utilize a vendor that provides for quantum orchestration across the enterprise to all nodes, communications and data. Features such as PQC policy management, key orchestration and backwards compatibility are elements that every organization should review so that implementation is seamless and much easier.
Photo Credit: The World in HDR / Shutterstock.com
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Quantum computing and its impact on cybersecurity [Q&A] - BetaNews
Old computer technology points the way to future of quantum computing Hope Standard – Hope Standard
Researchers have made a breakthrough in quantum technology development that has the potential to leave todays supercomputers in the dust, opening the door to advances in fields including medicine, chemistry, cybersecurity and others that have been out of reach.
In a study published in the journal Nature on Wednesday, researchers from Simon Fraser University in British Columbia said they found a way to create quantum computing processors in silicon chips.
Principal investigator Stephanie Simmons said they illuminated tiny imperfections on the silicon chips with intense beams of light. The defects in the silicon chips act as a carrier of information, she said. While the rest of the chip transmits the light, the tiny defect reflects it back and turns into a messenger, she said.
There are many naturally occurring imperfections in silicon. Some of these imperfections can act as quantum bits, or qubits. Scientists call those kinds of imperfections spin qubits. Past research has shown that silicon can produce some of the most stable and long-lived qubits in the industry.
These results unlock immediate opportunities to construct silicon-integrated, telecommunications-band quantum information networks, said the study.
Simmons, who is the universitys Canada Research Chair in silicon quantum technologies, said the main challenge with quantum computing was being able to send information to and from qubits.
People have worked with spin qubits, or defects, in silicon before, Simmons said. And people have worked with photon qubits in silicon before. But nobodys brought them together like this.
Lead author Daniel Higginbottom called the breakthrough immediately promising because researchers achieved what was considered impossible by combining two known but parallel fields.
Silicon defects were extensively studied from the 1970s through the 90s while quantum physics has been researched for decades, said Higginbottom, who is a post-doctoral fellow at the universitys physics department.
For the longest time people didnt see any potential for optical technology in silicon defects. But weve really pioneered revisiting these and have found something with applications in quantum technology thats certainly remarkable.
Although in an embryonic stage, Simmons said quantum computing is the rock n roll future of computers that can solve anything from simple algebra problems to complex pharmaceutical equations or formulas that unlock deep mysteries of space.
Were going to be limited by our imaginations at this stage. Whats really going to take off is really far outside our predictive capabilities as humans.
The advantage of using silicon chips is that they are widely available, understood and have a giant manufacturing base, she said.
We can really get it working and we should be able to move more quickly and hopefully bring that capability mainstream much faster.
Some physicists predict quantum computers will become mainstream in about two decades, although Simmons said she thinks it will be much sooner.
In the 1950s, people thought the technology behind transistors was mainly going to be used for hearing aids, she said. No one then predicted that the physics behind a transistor could be applied to Facebook or Google, she added.
So, well have to see how quantum technology plays out over decades in terms of what applications really do resonate with the public, she said. But there is going to be a lot because people are creative, and these are fundamentally very powerful tools that were unlocking.
Hina Alam, The Canadian Press
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Old computer technology points the way to future of quantum computing Hope Standard - Hope Standard
Quantum Computing Market Size, Scope, Growth Opportunities, Trends by Manufacturers And Forecast to 2029 This Is Ardee – This Is Ardee
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Quantum Computing Market Size, Scope, Growth Opportunities, Trends by Manufacturers And Forecast to 2029 This Is Ardee - This Is Ardee
Rigetti Computing to Report Second Quarter 2022 Financial Results and Host Conference Call on August 11, 2022 – GlobeNewswire
BERKELEY, Calif., July 19, 2022 (GLOBE NEWSWIRE) -- Rigetti Computing, Inc. ("Rigetti" or the "Company") (Nasdaq: RGTI), a pioneer in hybrid quantum-classical computing, announced today that it will release second quarter 2022 results on Thursday, August 11, 2022, after market close. The Company will host a conference call to discuss its financial results and provide an update on its business operations at 5:00 p.m. ET the same day.
Key details regarding the call are as follows:
Call Date: Thursday, August 11, 2022Call Time: 5:00 p.m. ET / 2:00 p.m. PT Webcast Link: https://edge.media-server.com/mmc/p/ndjhqqmyLive Call Participant Link: https://register.vevent.com/register/BI8f37a843026f4cbab4519e6d16db70d8
Webcast InstructionsYou can listen to a live audio webcast of the conference call by visiting the Webcast Link above or the "Events & Presentations" section of the Company's Investor Relations website at https://investors.rigetti.com/. A replay of the conference call will be available at the same locations following the conclusion of the call for one year.
Live Call Participant InstructionsTo participate in the live call, you must register using the Live Call Participant Link above. Once registered, you will receive dial-in numbers and a unique PIN number. When you dial in, you will input your PIN and be routed into the call. If you register and forget your PIN, or lose the registration confirmation email, simply re-register to receive a new PIN.
About RigettiRigetti is a pioneer in full-stack quantum computing. The Company has operated quantum computers over the cloud since 2017 and serves global enterprise, government, and research clients through its Rigetti Quantum Cloud Services platform. The Companys proprietary quantum-classical infrastructure provides ultra-low latency integration with public and private clouds for high-performance practical quantum computing. Rigetti has developed the industrys first multi-chip quantum processor for scalable quantum computing systems. The Company designs and manufactures its chips in-house at Fab-1, the industrys first dedicated and integrated quantum device manufacturing facility. Rigetti was founded in 2013 by Chad Rigetti and today employs more than 160 people with offices in the United States, U.K. and Australia. Learn more at http://www.rigetti.com.
ContactRebecca MalamudRigetti Computingpress@rigetti.com
Polly PearsonInvestor RelationsRGTI@investorrelations.com
Quantum Computing Use Cases: How Viable Is It, Really? – thenewstack.io
Use cases for quantum computing are still at an experimental stage, but were getting closer to meaningful commercialization of the technology. In a new research report, IonQ and GE Research (General Electrics innovation division) announced encouraging results for the use of quantum computing in risk management which potentially has wide applicability in industries like finance, manufacturing, and supply chain management.
I interviewed Sonika Johri, Lead Quantum Applications Research Scientist at IonQ, and Annarita Giani, Complex System Scientist at GE Research, to learn more about the current use cases for quantum computing.
In a blog post about the research, IonQ stated that we trained quantum circuits with real-world data on historical data indexes in order to predict future performance. This was done using hybrid quantum computing, in which some components of a problem are handled by a quantum computer while others are done by a classical computer. The results indicated that in some cases the hybrid quantum predictions outperformed classical computing workloads.
you need to model probability distributions and model complex correlations. And both of these things are things that quantum computers do really well.
Sonika Johri, IonQ
Johri explained that the analysis was done on stock market indices, on which they set out to model the correlations between them in order to make better predictions.
In order to solve a problem like this, she continued, basically, you need to model probability distributions and model complex correlations. And both of these things are things that quantum computers do really well.
When you measure quantum states, theyre just probability distributions, she said, and quantum entanglement is what allows you to generate or have access to complex correlations.
Giani, from the conglomerate General Electric, added that its not just about the stock market, when it comes to potential applications for these research findings. Its much more than that, she said. Imagine supply chain optimization. Imagine if you build an engine, how many suppliers have to come together. What is the risk of each supplier? Or indeed, measuring the risk of failure for each machine, or machine part, from a supplier.
I asked how the hybrid model worked for the stock market calculations which parts of the software program were quantum and which classical?
How it works is that you set up whats called an optimization loop, Johri replied. You use a quantum computer to calculate the value of some function, which is very hard for a classical computer to calculate [] and then you use the classical computer to run an optimizer that sends parameters to the quantum computer for the function its supposed to calculate, and then the quantum computer sends an answer back to the classical computer. This process is repeated on other values, hence the term optimization loop.
Essentially, the classical computer is outsourcing the hardest part of the calculation to the quantum computer, said Johri.
Both Johri and Giani think that quantum computing will remain a hybrid solution for some time to come.
Quantum computers are not good for doing one plus one, but theyre really good at sampling from probability distributions, is how Johri put it.
IBM and others in the industry have cited 1,000 qubits as the level at which quantum approaches can surpass classical computing (the so-called quantum advantage). So I asked Johri and Giani how long before the type of risk management calculations demonstrated in their research are available to commercial companies, like for instance GE?
We are looking at the industrial advantage [] what is it that could push our processes the way we build things, the way we maintain things.
Annarita Giani, GE Research
From the industrial point of view, said Giani, we are not looking at quantum advantage. We are looking at the industrial advantage, right. So what is it that could push our processes the way we build things, the way we maintain things. So at this point, we are very focused on use cases.
Giani added that doing research like this helps GE prepare for a time when quantum computing software and hardware is ready for commercialization. At that point, she said, GE will be ready to put it into production and scale solutions such as the risk management algorithms tested in this research.
On the hardware side, Johri thinks they will need to get to about 50 high fidelity qubits before the solution is competitive with classical computing approaches. As of February this year, IonQ had achieved 20 algorithmic qubits (#AQ), so she said there is still a lot of work to do.
But wait, IBM already has a 127-qubit quantum processor well above the 50 qubits Johri mentioned. I asked her how IBMs measurement compares to IonQs AQ?
Generally, not all qubits are made equal, and simply counting qubits does not give one the whole story regarding qubit quality or utility, she replied. There are many ways to compare the value of a systems qubits, but the best all start with running real algorithms on the system in question, because thats the thing we actually care about. She referred readers to this article on the IonQ blog for a more technical explanation.
Its also worth noting that IonQ has a different way of generating qubits than IBM. Whereas IBM uses superconducting, IonQ uses ions trapped in electric fields.
I asked Giani what other use cases GE is looking into for quantum computing?
We are interested in optimization as a big use case that touches all of our businesses, she replied. It can go from optimizing how a machine works, to optimizing a schedule inside the machine shop or global maintenance operations. Chemistry is another set of many different applications. New materials, for example energy storage for PV solar panels. And one particular domain, that touches many applications, that Im personally interested in we are pushing it inside GE is the fight [against] climate change.
We are interested in optimization as a big use case that touches all of our businesses.
Annarita Giani, GE Research
As an example of how quantum computing could help fight climate change, Giani mentioned forecasting. If we could forecast the climate, she said, given all the possible parameters, that will be a great advantage to help make a decision. Forecasting the supply of wind, solar and hydro resources will become more important for ensuring a stabilized grid, as more renewable resources are brought online.
Giani later forwarded me two research articles (1, 2) about climate change and quantum computing, and mentioned an upcoming workshop at IEEE Quantum Week in September on the topic (for any readers who would like to investigate further).
So how will companies in the near future access quantum computing? Johri expects it will be done via cloud computing platforms much like many of todays classical computing applications. IonQ will be providing the hardware for some of those platforms; as of today, IonQs machines are accessible via Microsoft Azure Quantum, Google Cloud and Amazon Braket.
In the next couple of years, or five years, well see the emergence of higher level quantum programming abstraction software.
Sonika Johri, IonQ
Finally, I asked the pair how easy it is for software developers to get into quantum computing?
Giani replied that GE Research did have quantum physicists on staff when it first began to explore quantum computing four or five years ago. However, she said that nowadays more software developers are getting involved.
If you are a software engineer with a great level of curiosity [and] an open mind, I think its possible, she said. You dont need to be a quantum physicist.
Johris outlook is a bit more cautious.
Programming quantum computers, its at a level thats even lower than machine code right now, she said. However, she does expect this to improve. In the next couple of years, or five years, well see the emergence of higher-level quantum programming abstraction software.
IonQ itself is focused on the hardware side, but Johri says that any quantum software that has any traction at all is integrated with IonQ systems, and is being used.
So there you have it, use cases like risk management and even climate change forecasting are starting to become viable for quantum computers. However, itll take several more years at least for this to be commercialized by GE and others.
Feature image via Shutterstock.
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Quantum Computing Use Cases: How Viable Is It, Really? - thenewstack.io