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What To Expect From Quantum Computing In The Next Two Years
There are many things we still don't know about 2022 and 2023, but one thing is certain: The quantum ecosystem will look very different in 2023 than it does now. In large part, this will be the result of quantum computers with more qubits and with less noise.
The number of qubits is not the only way to gauge the power of quantum computers — other factors such as coherence, fidelity and connectivity are just as important — but they provide a good ballpark of the power of quantum computation.
Today, the largest quantum computers have dozens of qubits. However, IBM plans to deliver a 1,121-qubit computer by 2023, and others have shared similar plans. This will cause significant change in the business landscape. Here's what the quantum world could look like with 1,000 qubits.
Classical machines will not be able to simulate 1,000-qubit computers.
Today, quantum computers have only shown limited computational advantages over classical computers. Quantum computers still have a small number of qubits, and classical computers are sufficiently large. Thus, any algorithm that runs on a 50-qubit quantum computer can be simulated on high-performance classical machines.
But, even at 100 qubits, with the expected coherency levels, it will be impossible for classical computers to simulate quantum ones. By introducing 1,000-qubit, high-fidelity computers, the chasm would widen and true quantum advantage for industrial-scale applications is expected to arise.
The need for quantum debugging will prompt adoption of new tools.
If 1,000-qubit computers can no longer be simulated, how can one debug algorithms running on them? Businesses using quantum will need to address this question.
The answer is, more than likely, by adopting new methods that will allow piecemeal simulation, simulation of smaller versions, mid-circuit exploration and other novel ways. Nevertheless, full verification of the quantum hardware or the algorithm running on it is unlikely.
This may become discouraging at first, but after gaining confidence with quantum computers it should not be a show-stopping issue. In fact, it precisely mimics the situation with high-end classical computers and algorithms, which can similarly not be verified in any mathematical rigor but are routinely trusted in practice.
The quantum computing focus will shift from academia and industrial research to industrial IT.
Most quantum work to date has taken place in academia and industry research organizations. That's because the industry is in an early stage. Plus, current quantum machines cannot yet deliver better results than classical computers. But with increasing qubit count, the business value of quantum will become more reachable, and enterprise deployments will accelerate.
Today, a classical computer can simulate the structure of a water molecule, but only larger quantum computers will accurately simulate more complex molecules. Chemistry experts are exploring how to use quantum to create new energy-efficient processes and produce better batteries. Logistics experts are exploring route optimization to save energy or gain efficiencies. Financial firms look to quantum to optimize portfolios and reduce risk.
1,000-qubit computers will enable multiple businesses to solve hard business problems that classical computers can't, which will drive additional enterprises to adopt quantum computing and prepare for the time it becomes a production technology.
Demand for quantum talent and better software platforms will soar.
Corporate customers with larger quantum aspirations will need to expand their quantum teams, while smaller players will begin work with quantum computing. Demand for quantum talent will significantly increase.
Harvard, MIT and many other universities already offer quantum information curriculums, and additional programs will be formed at colleges, universities and corporate training centers. My company's recent research indicates that professionals are hungry for quantum training. Could we train enough engineers to keep pace with the growing demand for talent?
The rise of software platforms that make quantum more accessible to people who know how to program but are not — at least not yet — quantum computing experts will help. Like common machine learning platforms, they shield users from the complexity under the hood. These quantum design platforms could help.
• Design sophisticated quantum circuits that take advantage of bigger hardware.
• Allow people who are not quantum Ph.D.s to make significant quantum contributions.
• Help your organization get value more quickly.
Quantum service bureaus will emerge.
Companies already sell quantum computer capacity. For instance, you can submit a quantum job to Amazon Braket and get results a few minutes later.
But once quantum computers can run sophisticated algorithms better than classical ones, we should see new "quantum algorithms as a service" products. For instance, use an API to submit a basket of stocks for optimization or the desired stops in a delivery route, and the service will return an optimized answer from the quantum computer.
Some businesses will deploy quantum on-premises.
Most quantum computers today are on the cloud because quantum computers involve significant investment, the hardware might become obsolete in several months and most quantum work is research work. But as quantum moves to production, enterprises may opt to own their own quantum computers to protect their quantum IP, ensure priority access and guarantee their response time.
Additionally, more nations will secure domestic quantum computing power to both limit their dependence and mitigate the risk of export restrictions enacted by the quantum computing superpowers.
Enterprises will share fewer of their quantum findings in academic papers.
Many academic papers are published today by organizations such as Wall Street firms. This is unlikely to last much longer. As quantum becomes increasingly strategic, companies are likely to keep their quantum innovations to themselves.
A healthy and diverse business ecosystem will emerge.
With universities opening quantum curricula, governments budgeting for quantum, multinational companies building up quantum agendas and venture investors seeking investment opportunities, the quantum ecosystem will grow at a pace comparable to the AI and alternative energy explosions.
Quantum computing concepts are decades in the making, but we are now seeing accelerated movements towards true business value. It's time to learn more about what will be possible in 2023 and beyond and implement this knowledge to the benefit of your business.
This article originally appeared in the Forbes Tech Council
There are many things we still don't know about 2022 and 2023, but one thing is certain: The quantum ecosystem will look very different in 2023 than it does now. In large part, this will be the result of quantum computers with more qubits and with less noise.
The number of qubits is not the only way to gauge the power of quantum computers — other factors such as coherence, fidelity and connectivity are just as important — but they provide a good ballpark of the power of quantum computation.
Today, the largest quantum computers have dozens of qubits. However, IBM plans to deliver a 1,121-qubit computer by 2023, and others have shared similar plans. This will cause significant change in the business landscape. Here's what the quantum world could look like with 1,000 qubits.
Classical machines will not be able to simulate 1,000-qubit computers.
Today, quantum computers have only shown limited computational advantages over classical computers. Quantum computers still have a small number of qubits, and classical computers are sufficiently large. Thus, any algorithm that runs on a 50-qubit quantum computer can be simulated on high-performance classical machines.
But, even at 100 qubits, with the expected coherency levels, it will be impossible for classical computers to simulate quantum ones. By introducing 1,000-qubit, high-fidelity computers, the chasm would widen and true quantum advantage for industrial-scale applications is expected to arise.
The need for quantum debugging will prompt adoption of new tools.
If 1,000-qubit computers can no longer be simulated, how can one debug algorithms running on them? Businesses using quantum will need to address this question.
The answer is, more than likely, by adopting new methods that will allow piecemeal simulation, simulation of smaller versions, mid-circuit exploration and other novel ways. Nevertheless, full verification of the quantum hardware or the algorithm running on it is unlikely.
This may become discouraging at first, but after gaining confidence with quantum computers it should not be a show-stopping issue. In fact, it precisely mimics the situation with high-end classical computers and algorithms, which can similarly not be verified in any mathematical rigor but are routinely trusted in practice.
The quantum computing focus will shift from academia and industrial research to industrial IT.
Most quantum work to date has taken place in academia and industry research organizations. That's because the industry is in an early stage. Plus, current quantum machines cannot yet deliver better results than classical computers. But with increasing qubit count, the business value of quantum will become more reachable, and enterprise deployments will accelerate.
Today, a classical computer can simulate the structure of a water molecule, but only larger quantum computers will accurately simulate more complex molecules. Chemistry experts are exploring how to use quantum to create new energy-efficient processes and produce better batteries. Logistics experts are exploring route optimization to save energy or gain efficiencies. Financial firms look to quantum to optimize portfolios and reduce risk.
1,000-qubit computers will enable multiple businesses to solve hard business problems that classical computers can't, which will drive additional enterprises to adopt quantum computing and prepare for the time it becomes a production technology.
Demand for quantum talent and better software platforms will soar.
Corporate customers with larger quantum aspirations will need to expand their quantum teams, while smaller players will begin work with quantum computing. Demand for quantum talent will significantly increase.
Harvard, MIT and many other universities already offer quantum information curriculums, and additional programs will be formed at colleges, universities and corporate training centers. My company's recent research indicates that professionals are hungry for quantum training. Could we train enough engineers to keep pace with the growing demand for talent?
The rise of software platforms that make quantum more accessible to people who know how to program but are not — at least not yet — quantum computing experts will help. Like common machine learning platforms, they shield users from the complexity under the hood. These quantum design platforms could help.
• Design sophisticated quantum circuits that take advantage of bigger hardware.
• Allow people who are not quantum Ph.D.s to make significant quantum contributions.
• Help your organization get value more quickly.
Quantum service bureaus will emerge.
Companies already sell quantum computer capacity. For instance, you can submit a quantum job to Amazon Braket and get results a few minutes later.
But once quantum computers can run sophisticated algorithms better than classical ones, we should see new "quantum algorithms as a service" products. For instance, use an API to submit a basket of stocks for optimization or the desired stops in a delivery route, and the service will return an optimized answer from the quantum computer.
Some businesses will deploy quantum on-premises.
Most quantum computers today are on the cloud because quantum computers involve significant investment, the hardware might become obsolete in several months and most quantum work is research work. But as quantum moves to production, enterprises may opt to own their own quantum computers to protect their quantum IP, ensure priority access and guarantee their response time.
Additionally, more nations will secure domestic quantum computing power to both limit their dependence and mitigate the risk of export restrictions enacted by the quantum computing superpowers.
Enterprises will share fewer of their quantum findings in academic papers.
Many academic papers are published today by organizations such as Wall Street firms. This is unlikely to last much longer. As quantum becomes increasingly strategic, companies are likely to keep their quantum innovations to themselves.
A healthy and diverse business ecosystem will emerge.
With universities opening quantum curricula, governments budgeting for quantum, multinational companies building up quantum agendas and venture investors seeking investment opportunities, the quantum ecosystem will grow at a pace comparable to the AI and alternative energy explosions.
Quantum computing concepts are decades in the making, but we are now seeing accelerated movements towards true business value. It's time to learn more about what will be possible in 2023 and beyond and implement this knowledge to the benefit of your business.
This article originally appeared in the Forbes Tech Council
About "The Qubit Guy's Podcast"
Hosted by The Qubit Guy (Yuval Boger, our Chief Marketing Officer), the podcast hosts thought leaders in quantum computing to discuss business and technical questions that impact the quantum computing ecosystem. Our guests provide interesting insights about quantum computer software and algorithm, quantum computer hardware, key applications for quantum computing, market studies of the quantum industry and more.
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