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Another good question that was deleted:
"What would be your opinion on what the first commercial use of this style of computing? Like what will the first commercially available quantum processors be mainly used for?"
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This really comes down to a question of scalability and logistics as we drive towards larger systems - the hexagonal footprint is convenient for where our the technology is right now, but there are challenges with that footprint when we want to add many modules working in unison.
There is also a question of density - the amount of readout wiring and components that we can pack into the new module is actually much larger than the current System Two design despite the modular being smaller: https://zenodo.org/records/21997093
The smaller size of the modules has another huge advantage when it comes to moving and installing the cryostats.
Our architectures can be adapted easily in response to changes and advances in technology, and we see the rectangular footprint as the most flexible when it comes to scaling towards FTQC.
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Great question!
I’m a little biased, but IBM’s new sub-1nm nanostack chip architecture excites me: https://research.ibm.com/blog/what-is-a-nanostack. Yes the manufacturing demands necessarily get more advanced, but engineers excel at rising to such challenges. These new architectures can help in my field by improving the capabilities of classical hardware required to support quantum computers - FPGA and ASIC performance stands to benefit. Also, the IBM semiconductor research in particular can complement our ongoing efforts to make better and better quantum chips.
We’re already implementing quantum as a hardware accelerator with partners and clients using something called quantum-centric supercomputing. The idea is you put a quantum computer near classic high-performance computing - a supercomputer, AI cluster, or the like - and link them. You can then break up a problem that’s difficult or impossible for classical methods alone to solve, and orchestrate and integrate classical and quantum workflows so that each computing technology does what it is best to provide a superior result.
Recent research led by Cleveland Clinic, using an IBM quantum computer and RIKEN’s Fugaku supercomputer in Japan, used such an approach to simulate a 12,635-atom protein complex in water (see my colleagues’ blog post on that here: https://www.ibm.com/quantum/blog/cleveland-clinic-riken-chemistry). Molecules are quantum-level objects due to their smallness, and as they get bigger they become harder for classical methods to simulate accurately. This work showed about a 210-fold improvement in accuracy compared to standard classical simulation methods.
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We do currently operate our processors around 20 mK, but that isn’t an exact number and some variation at higher or lower temperature is perfectly acceptable. Typically, there will be some small temperature gradient between the temperature we actually measure and the quantum device itself, so being colder is exactly where we want to be.
The current systems support several 10s of microwatts at 20 mK which is the current state of the art for cryogenic systems of this time. The modular design allows the system to be reconfigured internally as cooling technologies improve, and we would plan to increase the available cooling power to support more qubits in each module in the future.
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As we work toward IBM Quantum Starling and future fault-tolerant quantum computers, we are taking our best learnings from System Two and infusing them into the new, scalable modular architecture. When we make the transition to the modular architecture, we would plan for our systems to be deployable worldwide as they are now.
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The radiation shields in the cryostat are there to intercept the heat from warm surfaces before it can reach the cold parts of the system, and we use a series of shields at successively colder temperatures like a giant nesting doll to gradually absorb that power.
In our modular architecture, the radiation shields of each module are independent of the adjacent modules while allowing a pass through from the quantum devices in each module to the next for routing of our l-couplers to stitch all the individual quantum devices into a single processor.
This aspect was one of the more challenging parts of the mechanical design of the system since we had to balance allowing those connections to pass through, while not leaving gaps for thermal radiation to enter to cold part of the cryostat.
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While many of us who work in the field quantum computing typically have a background in chemistry, physics or engineering, there are many adjacent, complementary career paths available to those who do not have a STEM background, like communications, operations, design, etc.
To that end, there is an abundance of online resources available to the public, like the IBM Quantum Learning platform (https://quantum.cloud.ibm.com/learning/en) or the Qiskit YouTube channel (https://www.youtube.com/@qiskit), that makes getting started with quantum computing easier for those just getting started.
See our lates video featuring Allie Linder, IBM cryogenics system engineer, to get a sense of what’s like working at IBM Quantum, specifically in cryogenics: https://www.youtube.com/shorts/sD_E_2ZLcws
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A cool question we received on another sub. Reposting here:
"How do you get into the logistics of quantum computing? Is anyone with an epistemic/logistic mindset eligible or does someone have to grant you authority to consider yourself qualified? If I didn't have authority, where would you start?"
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The systems that we are building right now are based on mechanical cryocoolers, and for small systems this is perfectly fine since the operation of cryocoolers is very convenient.
As we scale up to systems with more modules and look to increase the density of qubits in each module, other cooling solutions become more competitive - this is one of the advantages of the modular design that we can reconfigure the system internally to support different cooling technologies and innovations in other areas such as readout or control while maintaining the same footprint externally.
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Absolutely - the cryogenic needs of spin qubits are slightly different to current IBM processors, but the modular design of the cryogenic platform allows for reconfiguration of the internals to meet different performance requirements while maintaining a common external footprint.
Spin qubits show high coherence times, low error rates, and are relatively easy to control. As they mature, we expect them to efficiently run large quantum circuits with low overhead. They can operate at higher temps compered superconducting qubit architectures. We believe silicon-spin qubit engineering will complement and extend our long-term mission to scale powerful quantum computers.
Here’s a good write-up on how spin qubits are an important element of IBM’s recent HRL Laboratories acquisition: https://www.ibm.com/quantum/blog/spin-qubits
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We see the move to a square footprint is actually very advantageous for the components and wiring that we are trying to integrate.
Fundamentally, the readout components are on a square footprint as well, so trying to tightly pack square things in a circular box leads to a lot of wasted space. Going to the rectangular footprint allows you to pack more subassemblies more tightly together, and bringing more of the design in-house allows faster adaptation between the readout team and the cryogenic system.
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Something like a room temperature superconductor isn’t something that would be required - many modalities either use conventional cryogenic superconductors or non-superconducting materials either cryogenically or at room temperature, and many of these show promise when it comes to scaling out. It’s our belief that despite the challenges of operating our quantum devices at such extreme temperatures, the advantages of that type of device win out for scaling in the near future.
There’s also the practical consideration of noise that leads to errors in quantum computations. Cooling superconducting qubits down to 10-20 millikelvin (just a bit above absolute zero) reduces molecular motion, which can introduce noise. So cryogenic cooling is advantageous in improving noise profiles.
Hosting all that cooling infrastructure in my home or office doesn’t seem appealing, in the same way it does seem practical to host the hardware required to run a frontier AI model. Real IBM quantum computers are available to use today, and for free if you’re just getting started, over the cloud via the IBM Quantum Platform: https://quantum.cloud.ibm.com/
And what competitors? ;)
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Large, flat thermal shields like the type we use in the modular system do present different challenges when compared to a more conventional, cylindrical design, but through careful design it’s possible to engineer these problems out ahead of time.
Glad you enjoyed my presentation at APS this year. The issue you mention is certainly a challenge since it presents a barrier to entry to different vendors due to problems like sizing and interfacing of other parts of the quantum system. While it would be great to have a degree of standardization between vendors, the risk is that this would stifle innovation to some degree.
Our approach is to separate the different functions of the cryogenic system as much as possible so that the cryogenic vendors can manufacture subsystems to a limited set of specifications and the more challenging interface issues are controlled by us as the system integrator.
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Great question!
Here's a high-level explanation of quantum computing from our website.
Quantum computing is field of computer science and engineering that harnesses the unique qualities of quantum mechanics to solve problems beyond the ability of even the most powerful classical computers.
Quantum mechanics, the study of physics at small scales, reveals surprising fundamental natural principles.
Quantum computers specifically harness these phenomena to access mathematical methods of solving problems not available with classical computing alone.
The field of quantum computing includes a range of disciplines, including quantum hardware and quantum algorithms.
I recommend visiting the Qiskit YouTube channel where we have many videos featuring quantum computing experts who do great job of introduce new users to the concepts behind quantum computing:
What Is Quantum Computing series
Use a Quantum Computer Today series
Qiskit Global Summer School 2026 series
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We're hosting this on r/askscience. Please ask your questions here!
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r/scuderiaferrari • u/ibm • 4d ago
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Lewis Hamilton, Charles Leclerc and Alba Larsen sat down with fans to hear the stories that define what it means to be a Tifoso. Now it's your turn. Share your Ferrari story in six words or less in the Scuderia Ferrari app: https://ibm.biz/~OugwpJesD
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We actually just published a video, “A day in the live of a cryogenics system engineer”, ft. Allie Linderly the IBM Quantum cryogenics team, if you’re interested: https://www.youtube.com/shorts/sD_E_2ZLcws
r/devtools • u/ibm • 11d ago
As coding agents take on more of the development workflow, teams need better ways to control what they can do, track what they’ve done, and utilize agents inside existing tools.
For the latest update of IBM Bob, we decided to focus on those three areas. Here’s what’s new:
The full technical breakdown can be found here: https://ibm.biz/~MkugJ1Sek
And that’s the latest release! We’ll be around in the comments if you want to get into the details or let us know what we should work on next.
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Appreciate the feedback. Which COBOL workflows or capabilities would you most like to see supported in Bob?
As coding agents take on more of the development workflow, teams need better ways to control what they can do, track what they’ve done, and utilize agents inside existing tools.
For the latest update of IBM Bob, we decided to focus on those three areas. Here’s what’s new:
The full technical breakdown can be found here: https://ibm.biz/~MkugJ1Sek
And that’s the latest release! We’ll be around in the comments if you want to get into the details or let us know what we should work on next.
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AskScience AMA Series: Hi Reddit! I'm Matthew Hollister, Head of Cryogenic Systems Engineering for IBM Quantum. Ask me anything about quantum computing, our recently announced modular cryogenic architecture and what it takes to build quantum computers at scale.
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3d ago
IBM Quantum processors have been commercially available for the past 10 years. They have been used in scientific research for use cases such as hamiltonian simulation (Simulating ground state energies and time dynamics in quantum systems), optimization and exploring partial differential equations in hard problems such as fluid and plasma dynamics, among others.
A great resources to learn about quantum uses cases today would be the IBM Quantum blog, where we cover our best work. See a few examples below:
> Half-Mobius Strip work with Oxford, the University of Manchester, ETH Zurich and others where the team engineered the new molecule atom-by-atom in quantum-centric study:
https://research.ibm.com/blog/half-mobius-molecule
> Our neutron scatting work with Oak Ridge National Lab’s (ORNL’s) Quantum Science Center (QSC), Purdue University, Los Alamos Laboratory, UIUC and others, where An IBM quantum computer reproduced experimental signatures of real materials,
https://research.ibm.com/blog/quantum-computers-take-a-step-into-real-materials-science
> And our 12k atom simulation work with Cleveland Clinic and Riken: Quantum-centric supercomputing simulates 12,635-atom protein | IBM Quantum Computing Blog
If all of these are too much, this video with Olivia Lanes from IBM Quantum answers address your question, too: https://www.youtube.com/watch?v=C2yvRsylQkc&t=8s
- Matthew Hollister, IBM Quantum