Frequently Asked Questions on Quantum Computing…Part 2
How does a quantum computer achieve fast processing?
Speed advantage from a quantum computer comes not from randomness, but rather, from the fact that quantum mechanics is based on amplitudes, and amplitudes work differently than probabilities. In particular, if an event can happen one way with a positive amplitude, and another way with a negative amplitude, those two amplitudes can “interfere destructively” and cancel each other out, so that the event never happens at all. The goal, in quantum computing, is always to set things up so that for each wrong answer, some of the paths leading there have positive amplitudes and others have negative amplitudes, so they cancel each other out, while the paths leading to the right answer reinforce. This set up can only be achieved for certain special problems. Those problems include a few with spectacular applications to cryptography, like factoring large numbers, as well as the immensely useful problem of simulating quantum mechanics itself.
What is it that we want out of a qubit?
For any system to be able to perform useful quantum computation utilizing a gate-based architecture it must satisfy strict conditions known as the Di Vincenzo criteria:
1. The system must be scalable with well-defined qubits.
2. The computer must have the ability to initialize the state of qubits.
3. Qubits must have long decoherence times.
4. The computer must be able to perform a universal set of quantum gates on the qubits.
5. It should be possible to measure the qubits.
Some of these criteria are rather obvious considering any implementation (e.g. criterion 1) while others are more stringent to realize. I should also emphasize again that these are the requirements for universal gate-based quantum computers and other architectures (e.g. quantum annealer) may have lesser requirements.
What does NISQ stand for?
This stands for “noisy intermediate-scale quantum.” Here “intermediate-scale” refers to the size of quantum computers that are now becoming available: potentially large enough to perform certain highly specialized tasks beyond the reach of today’s supercomputers. “Noisy” emphasizes that we have imperfect control over the qubits, resulting in small errors that accumulate over time; if we attempt too long a computation, we’re not likely to get the right answer.
It is now being demonstrated by Google, IBM, and others that it’s possible to build a quantum machine that’s large enough and accurate enough to solve a problem we could not solve before, heralding the onset of the NISQ era.
I see images of gold on quantum hardware and I think of a lot of money. Can a quantum computer be made in a cost-effective way that allows small companies to take part?
You’re probably seeing pictures of the dilution refrigerators used to cool solid-state quantum processors. The gold is a very thin plating on top of copper because it keeps the thermal contact resistance between components constant due to its low oxidation. Gold also has some favorable qualities when it comes to thermal and electrical conductivity. Dilution refrigerators cost several hundred thousand US dollars or more. The most expensive single component is not the gold, but the 3He that is used for cooling (it is much rarer and therefore expensive than 4He, which is the stuff you find in hot air balloons).
tl;dr. Quantum computers are currently insanely expensive, but that’s got almost nothing to do with the materials used — it’s expensive because it’s hard.
Are quantum computers prohibitively expensive to small companies/individuals?
The answer is basically yes, although some hardware start-ups aren’t associated with big corporations (notably Rigetti, IonQ, 1Qbit, D-Wave Systems, ID Quantique, ID QTEC, Silicon Quantum Computing, etc.).
If it were cheap it would imply that it’s easy to do. The technology is still in its infancy, and therefore it’s local that it’s not cheap or easy. Material costs are not significant for a current-generation quantum computer.
How do quantum computers compare to classical computers in terms of power consumption per logical operation?
For a quantum processor to exhibit quantum mechanical effects, you have to isolate it from its surroundings. This is done by shielding it from outside noise and operating it at extremely low temperatures. Most quantum processors use cryogenic refrigerators to operate, and can reach about 15 millikelvin–that’s colder than interstellar space. At this low temperature, the processor is superconducting, which means that it can conduct electricity with virtually no resistance. As a result, this processor uses almost no power and generates almost no heat, so the power draw of a quantum computer — or the amount of energy it consumes — is just a fraction of a classical computer’s.
“Most modern classical supercomputers use between 1 to 10 megawatts of power on average, which is enough electricity to meet the instantaneous demand of almost 10,000 homes. As a year’s worth of electricity at 1 megawatt costs about $1 million in the US, this leads to multimillion-dollar price tags for operating these classical supercomputers. In contrast, each comparable quantum computer using 25 kilowatts of power costs about $25,000 per unit per year to run.” Vern Brownell
Still, I am not convinced. What makes it so difficult to realize a universal quantum computer?
Developments in quantum computing and information processing are being hampered by very limited hardware: high error rates and challenges in achieving adequate coherence times required for computation. Today’s quantum computers can solve a selective niche of problems but a general-purpose, widely-usable, practical quantum computer will require advances in error correction, coupling a large number of qubits and possess long coherence times.
Quantum materials provide the environment where qubits, the elemental unit of quantum information processing, are defined and exist. Therefore, quantum materials are the basis of a quantum computer. To have a working quantum computer you need to couple together many qubits, while maintaining their long coherence time. These demands are often in conflict. The precision of the qubit materials is of major importance to solve these two challenging requirements. In this case, precision refers to materials uniformity in- chemical composition, and electronic transport properties.
The qubit is the most basic constituent of quantum computing, and also poses one of the most significant challenges for the realization of near-term quantum computers. Various characteristics of qubits have made it challenging to control them. Such imperfections in the control electronics can “impact the fidelity of the computation and thus limit the applications of near-term quantum devices.” The full promise of quantum computing (e.g. Shor’s algorithm for factoring) still requires technical leaps to engineer fault-tolerant logical qubits. Achieving a commercially viable quantum computer will require advancements across many pillars of the technology stack.
What is quantum supremacy and has it been achieved?
According to John Preskill, the term “quantum supremacy” describes the point where quantum computers can do things that classical computers can’t, regardless of whether those tasks are useful. Often abbreviated to just “quantum supremacy,” the term refers to the use of a quantum computer to solve some well-defined set of problems that would take orders of magnitude longer to solve with any currently known algorithms running on existing classical computers. The emphasis here is on being as sure as possible that the problem really was solved quantumly and is classically intractable, and ideally achieving the speedup soon (with the noisy, non-universal QCs of the present or very near future). If the problem is also useful for something, then so much the better, but that’s not at all necessary. When it is proved that the hardware is working, we can begin the search for more useful applications.
Read on Part 3 here
