Google claims their 54 qubit quantum computer can solve a problem in 200 seconds that would take a regular supercomputer 10,000 years but IBM says it would take 2.5 days or much less for a supercomputer to solve.
Nextbigfuture notes that disputes of Quantum Supremacy claims have happened before. D-Wave Systems had claims of quantum supremacy several years ago and researchers were able to use improved algorithms for the classical systems to speed up classical solutions. Programmers of classical computers are collectively very capable. During World War 2, code breakers were able to use the earliest primitive computer-like systems to break the German Enigma code machine. The German code machine had 158,962,555,217,826,360,000 combinations.
I expect that further refinements could bring a classical solution to this particular problem into the range of hours and minutes. Quantum computers will get faster and we will learn more about how to use them and when they are better. There will eventually be many problems where quantum computers are better and it will not be practical to make classical computer solutions. There will be large improvements in algorithms and science by competing with quantum and classical solutions.
Google’s Published Details on Their Quantum Supremacy Experiment
They made a new 54-qubit processor, named “Sycamore”, that is comprised of fast, high-fidelity quantum logic gates, in order to perform the benchmark testing. Our machine performed the target computation in 200 seconds, and from measurements in their experiment they determined that it would take the world’s fastest supercomputer 10,000 years to produce a similar output.
IBM disputed the level of the claim. IBM believes a regular non-quantum supercomputer with a lot of memory could perform the calculation in about 2.5 days.
IBM argues that an ideal simulation of the same task can be performed on a classical system in 2.5 days and with far greater fidelity. This is in fact, a conservative, worst-case estimate, and we expect that with additional refinements the classical cost of the simulation can be further reduced.
Nextbigfuture reviews the details of Google’s science first and then IBM’s science.
The Google Experiment
To get a sense of how this benchmark works, imagine enthusiastic quantum computing neophytes visiting our lab in order to run a quantum algorithm on our new processor. They can compose algorithms from a small dictionary of elementary gate operations. Since each gate has a probability of error, our guests would want to limit themselves to a modest sequence with about a thousand total gates. Assuming these programmers have no prior experience, they might create what essentially looks like a random sequence of gates, which one could think of as the “hello world” program for a quantum computer. Because there is no structure in random circuits that classical algorithms can exploit, emulating such quantum circuits typically takes an enormous amount of classical supercomputer effort.
Each run of a random quantum circuit on a quantum computer produces a bitstring, for example 0000101. Owing to quantum interference, some bitstrings are much more likely to occur than others when we repeat the experiment many times. However, finding the most likely bitstrings for a random quantum circuit on a classical computer becomes exponentially more difficult as the number of qubits (width) and number of gate cycles (depth) grow.
They first ran random simplified circuits from 12 up to 53 qubits, keeping the circuit depth constant. We checked the performance of the quantum computer using classical simulations and compared with a theoretical model. Once we verified that the system was working, we ran random hard circuits with 53 qubits and increasing depth, until reaching the point where classical simulation became infeasible.
This result is the first experimental challenge against the extended Church-Turing thesis, which states that classical computers can efficiently implement any “reasonable” model of computation. With the first quantum computation that cannot reasonably be emulated on a classical computer, we have opened up a new realm of computing to be explored.
The Sycamore Processor
The quantum supremacy experiment was run on a fully programmable 54-qubit processor named “Sycamore.” It’s comprised of a two-dimensional grid where each qubit is connected to four other qubits. As a consequence, the chip has enough connectivity that the qubit states quickly interact throughout the entire processor, making the overall state impossible to emulate efficiently with a classical computer.
The success of the quantum supremacy experiment was due to our improved two-qubit gates with enhanced parallelism that reliably achieve record performance, even when operating many gates simultaneously. They achieved this performance using a new type of control knob that is able to turn off interactions between neighboring qubits. This greatly reduces the errors in such a multi-connected qubit system. They made further performance gains by optimizing the chip design to lower crosstalk, and by developing new control calibrations that avoid qubit defects.
They designed the circuit in a two-dimensional square grid, with each qubit connected to four other qubits. This architecture is also forward compatible for the implementation of quantum error-correction. This 54-qubit Sycamore processor as the first in a series of ever more powerful quantum processors.
Future Google Quantum Work
1. Google will make their supremacy-class processors available to collaborators and academic researchers, as well as companies that are interested in developing algorithms and searching for applications for today’s NISQ processors. Creative researchers are the most important resource for innovation — now that Google has a new computational resource, they hope more researchers will enter the field motivated by trying to invent something useful.
2. Google is investing in their team and technology to build a fault-tolerant quantum computer as quickly as possible.
The particular notion of “quantum supremacy” is based on executing a random quantum circuit of a size infeasible for simulation with any available classical computer. Specifically, the preprint shows a computational experiment over a 53-qubit quantum processor that implements an impressively large two-qubit gate quantum circuit of depth 20, with 430 two-qubit and 1,113 single-qubit gates, and with predicted total fidelity of 0.2%. Their classical simulation estimate of 10,000 years is based on the observation that the RAM memory requirement to store the full state vector in a Schrödinger-type simulation would be prohibitive, and thus one needs to resort to a Schrödinger-Feynman simulation that trades off space for time.
The concept of “quantum supremacy” showcases the resources unique to quantum computers, such as direct access to entanglement and superposition. However, classical computers have resources of their own such as a hierarchy of memories and high-precision computations in hardware, various software assets, and a vast knowledge base of algorithms, and it is important to leverage all such capabilities when comparing quantum to classical.
When their comparison to classical was made, they relied on an advanced simulation that leverages parallelism, fast and error-free computation, and large aggregate RAM, but failed to fully account for plentiful disk storage. In contrast, our Schrödinger-style classical simulation approach uses both RAM and hard drive space to store and manipulate the state vector. Performance-enhancing techniques employed by our simulation methodology include circuit partitioning, tensor contraction deferral, gate aggregation and batching, careful orchestration of collective communication, and well-known optimization methods such as cache-blocking and double-buffering in order to overlap the communication transpiring between and computation taking place on the CPU and GPU components of the hybrid nodes.
In a recent paper, we showed that secondary storage can extend the range of quantum circuits that can be practically simulated with classical algorithms. Here we refine those techniques and apply them to the simulation of Sycamore circuits with 53 and 54 qubits, with the entanglement pattern ABCDCDAB that has proven difficult to classically simulate with other approaches. Our analysis shows that on the Summit supercomputer at Oak Ridge National Laboratories, such circuits can be simulated with high fidelity to arbitrary depth in a matter of days, outputting all the amplitudes.
IBM is concerned of where the term “quantum supremacy” has gone. The origins of the term, including both a reasoned defense and a candid reflection on some of its controversial dimensions, were recently discussed by John Preskill in a thoughtful article in Quanta Magazine. Professor Preskill summarized the two main objections to the term that have arisen from the community by explaining that the “word exacerbates the already overhyped reporting on the status of quantum technology” and that “through its association with white supremacy, evokes a repugnant political stance.”
Both are sensible objections. And we would further add that the “supremacy” term is being misunderstood by nearly all (outside of the rarified world of quantum computing experts that can put it in the appropriate context). A headline that includes some variation of “Quantum Supremacy Achieved” is almost irresistible to print, but it will inevitably mislead the general public. First because, as we argue above, by its strictest definition the goal has not been met. But more fundamentally, because quantum computers will never reign “supreme” over classical computers, but will rather work in concert with them, since each have their unique strengths.
For the reasons stated above, and since we already have ample evidence that the term “quantum supremacy” is being broadly misinterpreted and causing ever growing amounts of confusion, we urge the community to treat claims that, for the first time, a quantum computer did something that a classical computer cannot with a large dose of skepticism due to the complicated nature of benchmarking an appropriate metric.
For quantum to positively impact society, the task ahead is to continue to build and make widely accessible ever more powerful programmable quantum computing systems that can implement, reproducibly and reliably, a broad array of quantum demonstrations, algorithms and programs. This is the only path forward for practical solutions to be realized in quantum computers.
A final thought. The concept of quantum computing is inspiring a whole new generation of scientists, including physicists, engineers, and computer scientists, to fundamentally change the landscape of information technology. If you are already pushing the frontiers of quantum computing forward, let’s keep the momentum going. And if you are new to the field, come and join the community. Go ahead and run your first program on a real quantum computer today.
SOURCES- Science, IBM, Google, Nature
Written By Brian Wang, Nextbigfuture.com
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.