Per Gartner data, 20% of global organizations, including governments and companies, are expected to budget for quantum-computing projects by 2023, up from less than 1% in 2018. A 2020 paper by Inside Quantum Technology (IQT) projects that the quantum computing market will reach $2.2 Billion by 2026 as the number of installed quantum computers will reach around 180 over that same period.
A simple description of quantum computing, via MIT Technology Review, states that a classical computer utilizes bits that carry information represent either a 1 or a 0 (this is known as binary); but quantum bits, or qubits—which take the form of subatomic particles such as photons and electrons—can be in a kind of combination of 1 and 0 at the same time, a state known as “superposition.” Unlike bits, qubits can also influence one another through a phenomenon known as “entanglement.”
Using these two principles, qubits can exist in numerous different states and act as more sophisticated switches, enabling quantum computers to function in ways that allow them to solve difficult problems that are intractable using today’s computers. Quantum computing also has the potential to rapidly scale up its power, bypassing constraints that slowed the growth of traditional computers like Moore’s Law, which saw computing power double every 18 months to 24 months or so.
IBM’s Qubit Count, Google’s Time Crystal
Just the other day, IBM announced the company’s new Eagle processor more than doubles previous iterations of fully-programmable quantum computers by stringing together 127 qubits, making it the largest, and theoretically most powerful, superconducting quantum computer to be demonstrated. It was only 5 years ago that IBM was rolling out a 5-qubit quantum prototype. Looking down the line, Reuters notes that IBM is planning an "Osprey" chip in 2022 with 433 qubits and a "Condor" chip 1,121 qubits.
To contextualize the capacity of this processor, IBM says simulating Eagle would require more classical bits than there are atoms in every human being on the planet. Company executives believe the new chips will allow quantum systems to start outperforming classical computers in a variety of tasks within the next two years. IBM’s quantum tech has already been employed for enterprise use via the cloud for several years.
While we can easily demonstrate the superior power of quantum computers against classical computers, Engadget notes that it is more complex to compare quantum processors against one another based on number of qubits alone. Last October, for instance, Honeywell claimed its System Model H1 had a quantum volume of 128 with just 10 connected qubits versus IBM’s 27 qubit system with a quantum volume of 64.
IBM has yet to release a calculation of quantum volume for Eagle, but that may be due to their work on a new method of measuring a quantum computer’s speed. IBM posits that the number of qubits only reflects one of the three critical attributes of a quantum computer’s performance (the other two being speed and quality). As ZDNet writes, quantum volume measures quality, but circuit layer operations per second (CLOPS) is the first measure of speed that gauges the number of quantum circuits a quantum processing unit (QPU) can execute per unit of time. Although all of IBM’s quantum computers up to 65 qubits have a similar quantum volume, company researchers found vast differences in speed: the largest machine actually performed the slowest, at a CLOPS of 753 layers per second, compared to 1,419 for the smallest processor. This is likely an issue IBM has worked on in their new Eagle processor.
While Eagle has apparently vaulted IBM into the top position among companies working on fully-programmable quantum computing in terms of qubit volume, their processors are not yet at the point where it can solve problems that classical computers cannot.
Alphabet’s Google, also knee deep in quantum computing tech, made that claim back in 2019 with their quantum Sycamore system – a claim that was heavily disputed by competitors. In 2019, MRP broke down the facts and fiction behind their supposed achievement of “quantum supremacy”; the point at which a quantum computer that can perform a task beyond the reach of even the most powerful conventional supercomputer in any practical time frame.
While there is no denying that Google’s 56-qubit quantum machine did solve an extremely complex calculation in just 3 minutes and 20 seconds, 158 million times faster than the estimated 10,000 years it would have taken the world’s strongest supercomputer to do the same, the processor was built solely to solve this single equation, making it more of a laboratory experiment than something that would be marketable in the real world. Google has said it is on track to build a “useful, error-corrected quantum computer” by the end of the decade.
In the meantime, Google did have a significant breakthrough earlier this year that was truly unique. Using their quantum tech, the company demonstrated a genuine “time crystal”, a new category of phases of matter that remains “out-of-equilibrium” (being in a constant excited and evolving state) despite having perfect stability. As Quanta Magazine writes, a time crystal is an object whose parts move in a regular, repeating cycle, sustaining this constant change without burning any energy.
Once again, the question remains how time crystals will be applied to practical and commercial uses, but the fact that researchers are achieving quantum breakthroughs that were previously thought to be impossible shows we have not yet fully grasped the full potential of these rapidly growing processors.
Second Quantum SPAC Offering on Deck
As MRP highlighted earlier this year, quantum-computing startup IonQ Inc. became the first publicly-traded firm specifically focused on commercializing quantum-computing hardware, merging with blank-check firm dMY Technology Group Inc. III and listing on the NYSE. The Wall Street Journal noted that IonQ boasted a market cap of about $2 billion, having raised $734 million in funding since its founding in 2015, including $300 million through its planned merger and another $350 million in private investment funding from Hyundai Motor Co.
The company has given about 20 million software developers access to its current early-stage quantum-computing device through partnerships with cloud-computing service providers Amazon Web Services and Microsoft. CEO Peter Chapman has said the company will use the capital raised from going public to fund its efforts to build a 64-qubit chip by the end of 2023. Per Axios, Chapman claims those kinds of chips will eventually be able to be networked together to provide more than 1,000 qubits of processing power — the level many experts believe is required before quantum computers can reliably outperform cloud-accessible classical supercomputers.
IonQ began trading on October 1 and has skyrocketed 187% in its first month and a half of trading.
Rigetti Computing is the next quantum startup that plans to go public via SPAC merger – a deal with Supernova Partners Acquisition Company II valuing the company around $1.5 billion. Rigetti is expected to receive approximately $458 million in gross cash proceeds, including more than $100 million in private investment in public equity (PIPE). When the transaction closes Rigetti common stock is expected to be listed on the NYSE under the ticker “RGTI”. No date has yet been given for when that might be, however.
DataCenterNews reports the company expects to scale its quantum computers from its current 80 qubit Aspen-9 system to 1,000 qubits in 2024 and to 4,000 qubits in 2026. Currently, its systems scale to 80 qubits.
Interestingly, founder and CEO Chad Rigetti is an IBM alum. Rigetti reported revenue of $5.5 million for 2021, and a net loss of $26.1 million. However, it estimates revenue to grow to $288 million by 2025 and $594 million by 2026. |
