Zyvex Labs has the goal of Atomically Precise Manufacturing (APM). They are researching and developing tools for creating quantum computers, analog quantum simulation devices and other transformational systems that require atomic precision. Developed as part of this effort, ZyVector™ turns the world-class ScientaOmicron VT-STM into an STM lithography tool, creating the only complete commercial solution for atomic precision lithography.
Today, we find ourselves in a similar situation, in that our manufacturing tools can make quantum computers but not (as of yet) good enough to outperform classical computers. However, the situation today is radically different than 20 years ago. Moore’s law is grinding to a halt, and we know that quantum computers will eventually outperform even the most powerful classical digital supercomputers in a number of very important applications that will have a huge impact on our national security. Also different is the international competition to advance computing power. The US is poised to achieve dominance in quantum technologies, but only if we invest in improving the technologies to manufacture them. The US Government should work with the private sector to achieve dominance in quantum technologies because it would be incredibly risky to our economic health and national security not to do so. One of the best ways to dominate the technology sector is to lead the development of the technologies needed to manufacture superior technologies.
In particular, in the area of quantum computing, none of the currently popular approaches to manufacture quantum computers will be the dominant quantum computing technology that will yield the dramatic capabilities that have been promised. I do not doubt the wisdom of well-funded attempts to make the best quantum computers that we can with the current manufacturing tools. This is imperative so that we learn what can work in the short term and build from there. The three most popular types of qubits are 1)Superconducting, 2)Ion Trap, and 3)Semiconductor Quantum Dot qubits. We must recognize that these approaches each have significantly limiting aspects that make them unlikely to be the scalable approach that will become the dominant quantum computing technology in the long run.
Let me explain why I believe this to be true.
1) Superconducting qubits’ microwave resonators are huge, on the order of a square mm with limited downscaling prospects. Superconducting qubits also have modest “coherence times” (which will limit their computing power), and while they do have a solid state component, a Josephson Junction device; it is simply a non-linear element in a microwave resonator.
2. Ion trap qubits are smaller than Superconducting qubits but still huge compared with the transistors that run our current digital, non-quantum computers. Both approaches may be compared to the vacuum tube technology that was the original digital computing technology.
Just as classical computers started out with non-solid state devices (vacuum tubes) but transitioned to integrated solid state devices, integrated solid state devices will also become the dominant technology for quantum computers. Superconducting and ion trap qubits can each be thought of as the vacuum tube technology that classical computers started out with.
!!!HEY WHAT ABOUT 3) Semiconductor Quantum Dot Qubits??!!!
The problem with Semiconductor quantum dot qubits is that it appears that they can be manufactured in today’s modern semiconductor fabrication facilities. One would think that current semiconductor manufacturing equipment which is currently producing solid state devices with ~10nm minimum features should be the obvious choice to make quantum computers. However, semiconductor fabrication tools have poor relative precision, on the order of ± 10%, which is acceptable in non-quantum digital computers, but insufficient for quantum devices. Extremely complex classical digital circuits can nevertheless be created with this technology, because classical bits only have to distinguish between 0 and 1 and just have to be on either side of a threshold. It is a testament to semiconductor engineers that they can make such complex systems with essentially really sloppy relative precision.
Let me put this in a context that most people can appreciate. Back when I was in school, during a housing boom in Houston Texas, I worked one summer building houses and apartments. Imagine I am up on a roof and call down to my buddy Zeke: “Zeke, cut me a 10 foot rafter!” and Zeke sends me a rafter +/- one foot! Imagine what that house would look like. Try to imagine making a car with that sort of relative manufacturing precision.
To understand the importance of manufacturing precision to quantum computing (and why they are so powerful), you only need to know that while they have digital inputs and outputs (1s and 0s) that internally they deal with a superposition of 1 and 0 states that allows them to represent a much larger range of possible solutions than either 1 or 0 while they are in the quantum state. Today’s digital computers have to double the number of transistors to double their compute power, while you only have to add one qubit to double the power of a quantum computer. How the quantum calculations go on is very complicated, but physicists have figured out how to map meaningful problems onto quantum processes and this realization has led to an international race with very high stakes.
In order to effectively harness the power of quantum computers, we can no longer live with the sloppy fabrication of today’s semiconductor factories. Maintaining the specific mixture of the superimposed quantum states is crucial to the successful completion of quantum computation which requires much more precision that is currently available in manufacturing tools. Also, keep in mind that quantum phenomenon is expressed most strongly at the atomic scale and even atomic scale variations in the fabricated physical dimensions of these devices will make computation more difficult. This situation results in much more stringent fabrication tolerances for solid-state quantum devices. I speak from experience having worked on solid-state quantum devices[1,2].
I reiterate my belief that it is entirely appropriate to make the best quantum computers possible with the manufacturing tools that we presently have. However, if we do not, as a nation, at the same time invest in developing manufacturing tools that have significantly better manufacturing precision, we may come out strong in the first quarter but lose the game. We may have short term success in building Noisy Intermediate Scale Quantum (NISQ) computers but fail to develop the competitive scalable universal quantum computers that we seek.
There are many paths to developing higher precision manufacturing tools. It would be prudent to fund a large portfolio of R&D efforts. What follows is not intended to be a pitch for our particular approach, as much as an indication that there are paths to follow to much higher manufacturing precision.
Quantum effects are typically exhibited at atomic and molecular scales and that therefore the most capable quantum devices will be manufactured with atomic-scale precision. There are a number of approaches to atomically precise manufacturing and several are applicable to quantum computers and other quantum devices. We are not alone in this belief. The DOE is funding a portfolio of atomically precise manufacturing programs. Work at NIST and Oak Ridge National Laboratories, are exploring atomically precise manufacturing for quantum and other technologies.
One method that my company has commercialized and is further developing is a technology, referred to as hydrogen depassivation lithography (HDL). It is a next-generation form of e-beam lithography that is carried out with a Scanning Tunneling Microscope (STM). The technical details are available in the scientific literature, but let me point out graphically just how much more precise at patterning HDL is than the best conventional e-beam lithography can do. The graph compares the normalized radial distribution of conventional e-beam lithography with that of HDL. The data for the conventional e-beam lithography is taken from an excellent paper by Karl Berggren of MIT. I note that the conventional e-beam lithography distribution of dose must go out almost 4nm radially before the energy density drops to 10% of the maximum. With HDL the effective dose to expose drops 8 orders of magnitude at a radial distance of 0.5nm. HDL is a much sharper exposure tool. Sharp enough to do atomically precise patterning, and while it has other uses in solid-state quantum devices, it is being used to make single donor spin qubits. It is also amenable to scaling up through massive parallelism that is simply not possible with conventional e-beam lithography. Another approach being pursued at Oak Ridge National Laboratories is demonstrating atomic precision manipulation of matter with Scanning Transmission Electron Microscopes.
The US Government must invest in the future of our national security by funding research and development of an entirely new generation of manufacturing tools capable of atomic precision. I believe that this will be essential to achieve U.S. Dominance in quantum computing and many other valuable quantum technologies. I would be happy to provide many other details about the possibilities.
Reed, M. A., Randall, J. N., Aggarwal, R. J., Matyi, R. J., Moore, T. M., & Wetsel, A. E. (1988). Observation of discrete electronic states in a zero-dimensional semiconductor nanostructure. Physical Review Letters, 60(6), 535–537.
Broekaert, T. P. E., Randall, J. N., Beam III, E. A., Jovanovic, D., Seabaugh, A. C., & Smith, B. D. (1996). Functional InP/InGaAs lateral double barrier heterostructure resonant tunneling diodes by using etch and regrowth. Applied Physics Letters, 69(13), 1918–1920. https://doi.org/10.1063/1.117621
Manfrinato, V. R., Wen, J., Zhang, L., Yang, Y., Hobbs, R. G., Baker, B., … Berggren, K. K. (2014). Determining the resolution limits of electron-beam lithography: Direct measurement of the point-spread function. Nano Letters, 14(8), 4406–4412 https://doi.org/10.1021/nl5013773
Chen, S., Xu, H., Goh, K. E. J., Liu, L., & Randall, J. N. (2012). Patterning of sub-1 nm dangling-bond lines with atomic precision alignment on H:Si(100) surface at room temperature. Nanotechnology, 23(27), 275301 https://doi.org/10.1088/0957-4484/23/27/275301
Randall, J. N., Owen, J. H. G., Lake, J., Saini, R., Fuchs, E., Mahdavi, M., … Schaefer, B. C. (2018). Highly parallel scanning tunneling microscope based hydrogen depassivation lithography. JVSTB, 36, 6–10. https://doi.org/10.1116/1.5047939
Hill, C. D., Peretz, E., Hile, S. J., House, M. G., Fuechsle, M., Rogge, S., … Hollenberg, L. C. L. (2015). A surface code quantum computer in silicon. Science Advances, 1(9), e1500707–e1500707. https://doi.org/10.1126/sciadv.1500707
Kalinin, S. V., Borisevich, A. & Jesse, S. (2016). Fire up the atom forge. Nature, 539(7630), 485–487. https://doi.org/10.1038/539485a
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.