Publication Date: 23/09/2020

What is Quantum Computing (QC)?

Quantum computing harnesses the rules of quantum physics that hold sway over some of the smallest particles in the universe to build devices very different from today’s “classical” computer chips used in smartphones and laptops. Instead of classical computing’s binary bits of information that can only exist in one of two basic states, a quantum computer relies on quantum bits (qubits) that can exist in many different possible states. It’s a bit like having a classical computing coin that can only go “heads” or “tails” versus a quantum computing marble that can roll around and take on many different positions relative to its “heads” or “tails” hemispheres.
Because each qubit can hold many different states of information, multiple qubits connected through quantum entanglement hold the promise of speedily performing complex computing operations through interference. Currently, that might take thousands or millions of years on modern supercomputers. To build such quantum computers, some proponents have been using lasers and electric fields to trap and manipulate atoms as individual qubits whilst others have been experimenting with qubits made of loops of superconducting metal.

Why quantum mechanics?

Quantum mechanics is perhaps unrivaled as the most fascinating scientific discovery of the 20th century. Modern electronic devices that have changed the world of technology from lasers and magnetic resonance imagers (MRIs) to hard drives and liquid crystal displays (LCDs) owe their existence to the application of quantum mechanics.
The current challenge facing the information processing industry is to make more capable devices that are even smaller. Since the current best processors have approximately 14 billion transistors packed on a chip, the only way to keep improving technology is to reduce the transistor to the size of an atom. The laws of quantum mechanics dominate as the size of matter approaches nanoscale sizes. Matter at the atomic level reveals a world wholly unfamiliar to our senses, where atoms can pass through barriers and the act of observing an object can change its state.

What important quantum physics concepts should I know to appreciate how quantum computers work?

The most important concepts in quantum physics are superposition, entanglement, interference, and decoherence.
Superposition gives a quantum qubit possible states that go beyond just digital 1 or 0. The best analogy is a spinning coin where the spin is part of the equation for the state. It is from superposition that we get the exponential growth in the amount of data that can be handled during an active quantum computation. While 1 qubit contains two pieces of information, 10 qubits contain ²¹⁰ = 1024 pieces.
On the other hand, entanglement is a strange concept where two qubits, once they have been entangled, they will have the same synchronized state even when they are miles apart. Both superposition and entanglement are part of the famous thought experiment of Schrödinger’s cat.
Then, there is interference where the right answer is amplified by the interference of qubit states and wrong answers are canceled out. Interference is mainly a wave phenomenon that serves a very special role in the development of many qubit quantum computers. The power of a quantum processor is such that with enough high quality, usable qubits, we may be able to simulate and solve suitable complex problems.
Decoherence: Due to their small size quantum systems are very sensitive to their surroundings. Composite states due to superposition eventually diminish and finally collapse — and their desired quantum characteristics then disappear. This process is called decoherence and is one of the greatest challenges to be faced in quantum technology. The two forms of coherence are thermal relaxation and depolarisation. Relaxation is usually referred to as T1 and is a measure of how long it takes a
system to spontaneously move to ground state; depolarisation also called T2 which measures how long it takes the system to lose the superposition state. In building a quantum system we have competing interests: isolating the system from its surroundings to avoid decoherence and the need to be able to manipulate the system.
Superconductivity: A superconducting material has zero resistance when cooled below a certain temperature (no wonder why we talk of dilution refrigerators and temperatures around 10–15mK). Superconducting qubits are devices that are fabricated with superconducting materials separated by a thin layer of insulation material (Josephson Junction), operated in their superconducting state where they have well-defined energy levels that can be precisely manipulated.

What is the difference between a quantum computer and a classical computer?

Quantum computers are a radically different kind of computer-based on the laws of quantum mechanics. A classical computer manipulates bits (countless tiny electrical impulses to effect billions of microscopic transistors) to carry out a task whilst in a quantum computer computation is achieved through qubits (precise control of superposition and entanglement of electron spins or currents or polarization of photons).
In 2018, two technologies are used in most quantum computers (trapped ions and artificial “atoms” generated by superconducting circuits), but many different technologies are currently being explored for the basic physical implementation of qubits, or “physical qubits.”
That said, quantum computers have the potential to solve problems that scale up very fast and thus are intractable to classical computers.
Why are we so interested in quantum computers and quantum simulators?
The basic response is that quantum computers have certain problems they can handle much faster than classical computers. Hard problems are not only a question of whether they take a long time — the question is whether they can be solved at all and efficiently with available resources. The class of problems which quantum computation belongs to is called BQP (bounded-error quantum polynomial time).

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.

What about quantum advantage?

Quantum advantage is when a quantum computer can do a practical task sufficiently better than a classical computer to warrant switching between the technologies. Some argue chasing quantum supremacy is mostly a useless stunt since it has no practical application. It seems businesses hoping to sell quantum computers or access quantum computers — incline towards this view.

How do we quantify system performance in quantum computers?

There is no simple agreed-upon formula that fully describes the power of a quantum processor. All that can be said is that the higher the qubit count, quality level, and connectivity, the better. The number of logical qubits is a function of the specific error correction algorithm that is used with the physical qubits. It is not directly related to the qubit quality. However, the lower the qubit quality, the more error correction you may want to put in.
Counting the number of qubits in a quantum computer to determine computational power is too simplistic to be functionally useful — differences in how individual qubits are connected, how the qubits themselves are designed, and environmental factors make this type of comparison inequitable.
Quantifying system performance plays a key role in assessing the progress toward achieving “quantum advantage” — when for certain practical use cases, we can definitively demonstrate a significant performance advantage over today’s classical computers. As a measure of quantum computational power, increases in quantum volume correlate with the ability to solve larger, more complex problems across a range of disciplines.
In case you are interested according to IBM, the quantum volume is the largest computational space a quantum computing device can explore. It is measured by calculating the number of physical qubits, connectivity between qubits, and time to decoherence, as well as the available hardware gate set, and number of operations that can be run in parallel. This discrete quantity scales exponentially with the number of qubits. A system that successfully searches a four-qubit space has quantum volume ²⁴ = 16.
Before I go you may also hear of ‘quantum ready’ — it means to be prepared to take full advantage of the quantum computing era as it arrives.

Why is it so important to verify the performance of quantum hardware?

Current capabilities of qubits allow us to do simulation to a reasonable enough level of accuracy. Quantum computation is rather more demanding in terms of error correction. It’s because precisely controlling a quantum computer is notoriously difficult. In a sense, merely looking at a quantum system unavoidably disturbs it, a manifestation of Heisenberg’s famous uncertainty principle. So if we want to use such a system to store and reliably process information, we need to keep that system nearly perfectly isolated from the outside world. At the same time, though, we want the qubits to interact with one another so we can process the information; we also need to control the system from the outside and eventually measure the qubits to learn the results of our computations. It is quite challenging to build a quantum system that satisfies all of these desiderata, and it has taken many years of progress in materials, fabrication, design, and control to get where we are now.
The apparent quantum supremacy achievement marks just the first of many steps necessary to develop practical quantum computers. The fragility of qubits makes it challenging to maintain specific quantum states over long periods when performing computational operations. That means it’s far from easy to cobble together large arrays involving the thousands or even millions of qubits that will likely be necessary for practical, general-purpose quantum computing.
Such huge qubit arrays will require error correction techniques that can detect and fix errors in the many individual qubits working together. A practical quantum computer will need to have full error correction and prove itself fault-tolerant — immune to the errors in logical operations and qubit measurements — to truly unleash the power of quantum computing.

If quantum supremacy was achieved, what would it mean for the QC community?

The next milestone would be to achieve quantum computational supremacy and useful quantum error-correction in the same system. Perhaps, firstly we may want to use a programmable QC, with qubit count in the range of 50 to 100 to do some useful quantum simulation (say, of a condensed-matter system like NV centers in diamond) much faster than any known classical method could do it. A second obvious milestone would be to demonstrate the use of quantum error-correction, to keep an encoded qubit alive for longer than the underlying physical qubits remain alive.

Is quantum annealing the same as quantum computing?

The difference between a quantum annealer and quantum computer is that a computer is a fully programmable device — one that you can program with an arbitrary sequence of nearest-neighbour 2-qubit gates, just by sending the appropriate signals from your classical computer whilst a quantum annealer is useful for a single type of calculation called “quadratic unconstrained binary optimization (QUBO)”. General-purpose quantum computers can be used for a wider variety of calculations.

Is the future of computation hybrid?

There are two approaches to hybrid; hybrid quantum computer and hybrid computer (classical computer combined with a quantum computer).
Hybrid quantum computers: Qubits themselves are incredibly powerful, yet delicate. They quickly lose their special quantum properties, typically within 100 microseconds (for state-of-the-art superconducting qubits), due in part to electromagnetic environment, vibrations, and temperature fluctuations. To make quantum computers more reliable and stable there is a need to harmoniously combine different technologies that complement each other.
Hybrid computer: What’s meant here is not just making control electronics more efficient and nearby (lowering latency) but optimizing algorithms such that the portions best suited for the quantum processor are run on it while other portions are optimized for classical systems. All quantum computers are blended systems in which classical computers play an essential role. Accenture has patents to that effect. Hybrid computing means utilizing the best of both the quantum and classical worlds, and lowering the barriers for companies of all sizes to get started using quantum computers.

Will a universal quantum computer when realized break any encryption code?

First, the devices currently being built have 50–100 qubits and no error-correction. Running Shor’s algorithm to break the RSA cryptosystem would require several thousand logical qubits. With known error-correction methods, that could easily translate into millions of physical qubits, and those probably of a higher quality than any that exist today. None of the systems we know of is close to that, and we have no idea how long it will take.
Secondly, even assuming we have scalable, error-corrected QCs, on our current understanding they’ll only be able to crack certain codes, not all of them. By an unfortunate coincidence, the public-key codes that they can crack include most of what we currently use to secure online communication. However, symmetric-key crypto should only be minimally affected. There are even ideas of public-key cryptosystems based on lattices that no one knows how to break despite years of trying, and efforts are now underway to migrate to those systems.

Where are we with quantum computing today?

Today’s quantum computers include thousands of parts that work together to harness qubits to perform quantum computations albeit with errors and limitations. It is, however, possible to access real quantum computers through the cloud to optimize their performance, conduct research and explore new problems.

I am familiar with Moore’s law but I now hear there is also Neven’s law?

Unlike Moore’s Law that has predicted classical computing power will approximately double every two years — exponential growth — Neven’s Law describes how quantum computing seems to gain power far more rapidly through double exponential growth.
Doubly exponential growth is far more dramatic. Instead of increasing by powers of 2 (2⁰,2¹,2²…) quantities grow by powers of powers of 2 [(2²)⁰,(2²)¹,(2²)²…]. Doubly exponential growth is so singular that it’s hard to find examples of it in the real world. The rate of progress in quantum computing may be the first. The doubly exponential rate at which, according to Neven, quantum computers are gaining on classical ones is a result of two exponential factors combined. The first is that quantum computers have an intrinsic exponential advantage over classical ones: If a quantum circuit has four quantum bits, for example, it takes a classical circuit with 16 ordinary bits to achieve equivalent computational power. This would be true even if quantum technology never improved.
The second exponential factor comes from the rapid improvement of quantum processors. The best quantum chips have recently been improving at an exponential rate. This rapid improvement has been driven by a reduction in the error rate in the quantum circuits. Reducing the error rate has allowed the engineers to build larger quantum processors. If classical computers require exponentially more computational power to simulate quantum processors, and those quantum processors are growing exponentially more powerful with time, you end up with this doubly exponential relationship between quantum and classical machines. While the exact rate at which quantum computers are closing in on classical ones might be debatable, there’s no doubt quantum technology is improving, and fast.

Is there anything like quantum internet? Why do we need to do that?

The quantum internet is a network for transmitting qubits between distant locations. These “qubits” might be made of photons that are in a combination of two different polarizations. The ability to send qubits from one place to another over fiber-optic cables might not transform society as thoroughly as the classical internet, but it would once again revolutionize many aspects of science and culture, from security to computing to astronomy.
The idea is not to replace the internet we have today but really to add new and special functionality. While it is hard to predict all uses of the future quantum, several major applications seem feasible and these include secure communication, clock synchronization, extending the baseline of telescopes, secure identification, achieving efficient agreement on distributed data, exponential savings in communication, quantum sensor networks, as well as secure access to remote quantum computers in the cloud.

What makes quantum keys so secure?

A good way to understand what a quantum internet can do is to think about “quantum entanglement,” a special property that two quantum bits can have that makes all of this possible. The first property of entanglement is that it’s “maximally coordinated”: Distant qubits entangled through the use of the quantum internet ensure that a measurement on one of the qubits guarantees the same outcome on the other one even though the outcome wasn’t determined ahead of time. In this way, the quantum internet is very good for tasks that require coordination, due to that first property of quantum entanglement. The interesting part is the fact that this entanglement cannot be shared with other people. So the second property of entanglement is that it’s inherently private. Nothing else can have any share of that entanglement. And this is the reason why quantum communication is so good for problems that require security.

Who is driving quantum computing development?

Microsoft, Intel, Rigetti, IonQ, IBM, Google, Alibaba, Hewlett Packard, Tencent, Baidu, and Huawei are investing in quantum computing as organizations.
The European Union in 2018 pledged $US1,1 billion towards research in the field and similar public-investment initiatives from the United States, United Kingdom, Japan, Sweden, Singapore, Canada, Australia, and China are all plowing hundreds of millions of dollars into quantum technologies.

Which are the topical areas of quantum information theory?

Quantum physics has taken center stage as a powerful way to harness the laws of nature to solve certain problems. Various professionals from the fields of Physics, Computer Science, Mathematics, Engineering, and Information Theory are coming together to cope with the demands of this new and promising field.

Quantum algorithms & complexity

Quantum processors are very useful in implementing quantum algorithms. Quantum algorithms work on universal quantum computers and allow for processing speeds that exceed known classical algorithms. The development of robust quantum algorithms has been somewhat slow, in part due to the challenge of retrieving the answer from our quantum computer. Popular quantum algorithms include Shor’s algorithm, Grover’s algorithm, Deutsch–Jozsa algorithm, Simon’s algorithm, and Quantum phase estimation algorithm amongst others. Scientists are working on new techniques and protocols. The ability to use a quantum system to perform simulation is very crucial in quantum information theory research. There are a variety of models & architectures for quantum systems available online from a variety of big and small players like Rigetti, Alibaba, IBM, D-Wave among others. These players are provoking renewed interest in science and engineering. Quantum algorithms are being developed and tested and new physical implementations are being considered.
Topological approaches: Topological methods are one of many pathways being considered as the world attempts to build a universal and scalable quantum processor. Their main attraction is based on their intrinsic fault-tolerant properties that make active error detection and recovery unnecessary. However, their drawback is that they have longer operation times, such that there is still so much more work to be done to identify the available schemes that are well suited for quantum computation.
Companies like Microsoft are supporting research efforts in this space.
Quantum simulations: Developments in the field of quantum technology suggest that quantum simulators are becoming the first short-term application of quantum computers. The benefit of quantum simulators stems from the fact that they offer a platform to test thoughts and ideas involving quantum mechanics which their classical peers struggle to handle, and they can deliver on this with modest hardware capabilities. To build a useful quantum processor more stringent requirements have to be met. There are a variety of problems where simulators can be employed immediately like in chemical simulation, drug discovery, artificial intelligence, process optimization, high energy physics, and condensed matter physics.
Quantum error correction & purification: Quantum materials provide the environment where qubits, the elemental unit of quantum information processing, are defined and live. 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.
Qubits that are hard to couple together have long coherence time because they tend to achieve adequate levels of isolation. On the other hand, systems that are easy to couple together tend to decohere quickly, because they can be perturbed easily by the environment. The precision of the qubit materials is of major importance to solve these two challenging requirements.
Multi-partite entanglement & applications: To build a universal scalable quantum computer, it should be possible to achieve multi-particle entanglement. The ability to achieve that will have a profound impact on the ability to implement novel protocols in quantum information processing. Multipartite entangled states represent keys resources, both for quantum computers and for novel communication schemes with several users such as quantum-secret sharing, quantum voting, etc. Alternatively one can consider multi-partite fingerprinting schemes that would allow for the determination of whether or not many databases are identical with very little resources. Further, solid-state lattice platforms can prove useful in building hybrid quantum systems.
Quantum Communication: For any system to deliver value it has to be scalable. The ability to move quantum data from one place to another within the local system as well as with other remote systems is called quantum communication. At the basic level quantum states encode quantum information: hence quantum communication means the transmission of quantum information as well as the distribution of quantum resources such as entanglement. Quantum Communication covers aspects ranging from elementary physics to practical applications that are relevant to society today. From an application point of view, a major interest has been focused on Quantum Key Distribution (QKD), as this offers a provably secure way to establish a confidential key between distributed partners.
While a quantum computer can use a small number of qubits to represent an exponentially larger amount of data, there is not currently a method to rapidly convert a large amount of classical data to a quantum state (this does not apply if the data can be generated algorithmically). For problems that require large inputs, the amount of time needed to create the input quantum state would typically dominate the computation time and greatly reduce the quantum advantage. While there are proposals for quantum random access memory (QRAM) that can perform this function, it seems there aren’t any practical implementation technologies.
tl;dr. In summary research in the field focuses on quantum computing hardware, software, algorithms, and applications.s

I am optimistic that the first applications are going to be in the domain of quantum simulation where we use a quantum computer to simulate a quantum system.
Thanks in part to hybrid computing, early quantum applications are already being used in industries including automotive, manufacturing, and finance. Volkswagen is using quantum computers to build early applications that will be able to optimize public transportation routing in cities around the world. DENSO, a leading auto-parts manufacturer based in Japan, has reported that it can reduce gridlock and improve the efficiency of autonomous robots on its factory floors with the help of an application built with a quantum computer. Quantum computing has the potential to yield a paradigm shift in flight physics, one that could forever alter how aircraft are built and flown.
Airbus is running challenges based on quantum computing to assess how this burgeoning computational technology could be included or even replace other high-performance computational tools that, today, form the cornerstone of aircraft design.
Below I list corporations involved in the development of commercialized quantum computing hardware, quantum software, quantum cryptography, and quantum communication.
AT&T
Baidu
Booz | Allen | Hamilton
British Telecommunications
Honeywell
KPN
Lockheed Martin
Mitsubishi
NEC
Nokia
NTT
Raytheon
SK Telecom
Toshiba
Generally, quantum computers are earmarked for applications in cryptography, simulation of the universe at the atomic scale, and possibly even give crucial insights about quantum gravity.

How can I get access to a quantum computer?

There has been a lot of progress in the field of quantum information processing and emerging online platforms now offer an opportunity to digitally experiment and gain valuable insights in quantum-based technologies.
Currently, anyone can write their quantum program by accessing quantum systems over the cloud-like using the IBM Q Experience.
Still, if you want to you can sign up for access to Alibaba, Rigetti, Quantum Inspire, QUI and also use theirs for free. More resources here.
Is the quantum computer available online an actual quantum computer or a software emulation?
It is not a simulation of a quantum computer. It is quantum computing hardware. We write a program that we then send to this cloud quantum computer at IBM for example and they will implement it there on their quantum computer and send the results back. Most of the platforms I know give access to both; a quantum simulator to help check circuit integrity and a real quantum device for actual results.

Who should be interested in quantum computing?

You don’t have to be a quantum physicist or work in a lab to get involved in quantum computing. Quantum computing is still in its infancy and there are many ways computer scientists, coders, mathematicians, scientists, quantum enthusiasts, and tinkerers can all contribute to progress in this emerging field. Anyone who can invest in understanding the basic science behind quantum computing and has the time and resources to learn more can participate with different skills and levels of expertise to explore the field.
Even with just a few introductory quantum programming skills, you can contribute and help tackle problems like developing efficient compilers that optimize quantum circuits to run on real devices or even build a quantum computer game.

What knowledge is required to grasp quantum computing?

There are courses available on EdX, Coursera, MIT, Future Learn, and Udemy that start from the basics but they are usually lighter if you’ve had a course in quantum mechanics and linear algebra at some point. Further, it’s also an added advantage if you’ve programmed a computer in some way before. However, you shouldn’t be discouraged if you are willing to put in a few hours to learn some quantum physics, linear algebra, and computer science.

I am interested in quantum computing research. Any topic suggestions?

Given that there is significant work that remains before a quantum computer with practical utility can be built, there is a need for technological advances in the following key areas:
· Decreased qubit error rates to better than 10–3 in many-qubit systems to enable quantum-error-correction (QEC).
· Interleaved qubit measurements and operations.
· Scaling the number of qubits per processor while maintaining/improving qubit error rate.
· Development of methods to simulate, verify and debug quantum programs.
· Creating more algorithms that can solve problems of interest, particularly at lower qubit counts or shallow circuit depths to make use of NISQ computers.
· Refining or developing quantum-error-correcting-codes (QECCs) that require low overhead; the problem is not just the number of physical qubits per logical qubit, but to find approaches that reduce the large overheads involved with implementing some operations on logical qubits (for example, T-gates or other non-Clifford gates in a surface code) take a very large number of qubits and steps to implement.
· Identifying additional foundational algorithms that provide algorithmic speedup compared to classical approaches.
· Establishing inter-module quantum processor input and output (I/O).

Which professions can be found in quantum computing?

Like any other field, diversity of backgrounds and experiences are equally important in quantum computing resulting in opportunities for researchers, engineers, developers, designers, technicians and domain experts. To be particular the field is driven by condensed matter physicists, quantum engineers, quantum microwave engineers, quantum computer architects, quantum algorithms researchers, quantum theorists, quantum cryogenic engineers, quantum FPGA engineers, quantum software developers, quantum community builders, and user experience designers.
Anything else
The field of quantum computing has seen a lot of progress and is thus broadening thereby creating a lot of entry pathways. This opens doors for lots of opportunities to contribute to the future of the field. Here are some useful links for a quantum enthusiast who wants to learn or get involved: Quantum Stack Exchange, Qiskit, Quantiki, Reddit, Medium, Github, Quantum Algorithm Zoo and there is a free textbook here.

In conclusion

Quantum computing is showing signs of early benefits today, but there’s more to do before we see its full practical deployment. We need continued buy-in and investment from both governments and businesses to achieve widespread adoption. This can only happen if the technology finds important applications with demonstrable benefits. We also need to train and develop the next generation of expertise and talent in the quantum workforce. Finally, we need to continue breaking down barriers to using quantum computers with affordable, flexible cloud access and developer-friendly software and tools.
Nevertheless, even if a universal quantum computer is not successfully realized, understanding quantum computing and quantum technologies expand the boundaries of humanity’s scientific knowledge, and the results could transform our understanding of the universe.
Quantum computers are unlikely to be useful as a direct replacement for conventional computers, or all applications; rather, they are currently expected to be special-purpose devices operating in a complementary fashion with conventional processors, analogous to a co-processor or accelerator.