Technology Advancement

Quantum Computing: Definition, How It’s Used, and Example

Another area where drug discovery could see a boost from quantum computing is protein folding. Startup ProteinQure — which was featured by CB Insights in the 2020 cohorts for the AI 100, and Digital Health 150 — is already tapping into current quantum computers to help predict how proteins will fold in the body. But using quantum computing to address the issue could ultimately make designing powerful protein-based medicines easier. For example, Google recently announced that it had used a quantum computer to simulate a chemical reaction, a milestone for the nascent technology.

Quantum Computing

He’d love to see someone build a machine that proves the naysayers wrong. Last month, Aaronson fretted on his blog Shtetl-Optimized that the hype, which he has been countering for years, has gotten especially egregious lately. Despite all this progress, it’s early days for the whole field, and most
researchers agree that we’re unlikely to see practical quantum
computers appearing for some years—and more likely several decades. Quantum computers need to protect qubits from external interference, either by physically isolating them, keeping them cool or zapping them with carefully controlled pulses of energy. Additional qubits are needed to correct for errors that creep into the system.

From the report

This can, for example, be utilized in construction works for subsoil mapping before construction, or to predict earthquakes. Other sensors measure magnetic fields from, for example, muscle activity and nerve paths and have great potential in fields such as medical diagnosis. Magnetic field sensors can also be used for military purposes like navigation. But NISQ computers’ R&D practicality is demonstrable, if decidedly small-scale. That’s a small enough molecule that it can also be simulated using a supercomputer, but the quantum simulation provides an important opportunity to “check our answers” after a classical-computer simulation.

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There’s also the fundamental issue of how you get data in and out of a quantum computer,
which is, itself, a complex computing problem. Some critics believe these issues are insurmountable;
others acknowledge the problems but argue the mission is too important to abandon. Apart from Shor’s algorithm, and a search method called Grover’s algorithm, hardly any other algorithms have been discovered that would
be better performed by quantum methods. Given enough time and
computing power, conventional computers should still be able to solve
any problem that quantum computers could solve, eventually. In
other words, it remains to be proven that quantum computers are
generally superior to conventional ones, especially given the difficulties of
actually building them.

What can quantum computers do that ordinary computers can’t?

In such a state, changing one qubit directly affects the other in a manner that’s predictable. IBM’s quantum computers are programmed using Qiskit (link resides outside, our open-source, python-based quantum SDK. Our quantum computers use Josephson junctions as superconducting qubits. By firing microwave photons at these qubits, we can control their behavior and get them to hold, change, and read out individual units of quantum information.


A handful of quantum computers are now in operation, and a few are available for experimentation through the cloud, but they are still works in progress. For one thing, these computers have qubits in the hundreds, whereas several thousands or even millions of qubits are needed for hard problems. Another challenge is that qubits are difficult to manufacture, and some of the qubits won’t behave as expected, requiring researchers to add extra qubits for quantum error correction. The variety of ways of producing qubits underscores the state of quantum computing today.

The Princeton initiative will offer fellowships for graduate students and postdoctoral researchers, and research and educational opportunities for undergraduates. Raising money today is more challenging, said Asif Sinay, chief executive of Qedma, whose error suppression technology is designed to help squeeze more power out of quantum computers. But he’s more sanguine about the situation since he’s not looking for investors right now. It’s a long-term plan with an expectation that it’ll be able to solve life sciences problems in 2035, said physicist Peter Krogstrup Jeppesen, who left a quantum computing research position at Microsoft to lead the effort. The technology could be big and disruptive, and that piqued the interest of investors. Over the past 14 months, three quantum computer makers took their companies to the public markets, taking the faster SPAC, or special purpose acquisition company, route rather than a traditional initial public offering.

That recommendation comes from Konstantinos Karagiannis, director of quantum computing services at consulting firm Protiviti. Classical encryption effectively protects all financial information that banks and credit unions use and exchange. Banks protect their transactions, trade secrets and every other piece of their business with classical encryption, though that is not the only layer of protection they use. They also hide this data behind layers of authentication technology, data fragmentation and other strategies that make it hard to access. Most dastardly among those impacts is the ability for cybercriminals to decrypt any data that is protected only by classical cryptography, which includes any data they collect before achieving that capability. FS-ISAC described this strategy, dubbed “harvest now, decrypt later,” as threat actors hoarding encrypted data intercepted today as they wait to decrypt it with quantum computers.

Kicking the quantum computing tires

“All of the other use cases that people talk about are either more marginal, more speculative, or both,” says Scott Aaronson, a computer scientist at the University of Texas at Austin. Quantum specialists have yet to achieve anything truly useful that could not be done using classical computers. Over the past year, QCI has built and tested multiple hybrid AI hardware systems using photonics and quantum mechanics to boost machine learning efficiency, reduce the power consumption, and significantly speed up the training. Those systems have demonstrated substantial advantages over existing digital electronic hardware for many AI applications.

When scientists want to do things like harness the power of molecules during photosynthesis, they won’t be able to do so using regular old computers. They need to use quantum computers, which are able to measure and observe quantum systems at the molecular level as well as solve the conditional probability of events. Basically, quantum computers can do billions of years worth of computing over the course of a weekend — and untangle some of the world’s most complex problems in the process.

What does the quantum computing landscape look like?

And a quantum hardware system is about the size of a car, made up mostly of cooling systems to keep the superconducting processor at its ultra-cold operational temperature. This new system allows the atoms to be assembled in two-dimensional arrays of optical tweezers. Using the tweezers, researchers can arrange the atoms in defect-free patterns and create programmable shapes like square, honeycomb, or triangular lattices to engineer different interactions between the qubits.

How Do Quantum Computers Work?

Both the Bristol Quantum Information Institute and its Quantum Engineering Technology labs help make the university one of the top places to get a Ph.D. or masters in quantum computing. The Quantum Engineering Technology Labs develop prototypes for quantum applications, from computing to sensing to simulations. With a group of mentors and advisors, students of this quantum computing degree program will learn more about the career paths within this field and be assisted in their journey. The so-called T1 lifetime and T2 dephasing time are a time to characterize the physical implementation and represent their sensitivity to noise. A higher time does not necessarily mean that one or the other qubit is better suited for quantum computing because gate times and fidelities need to be considered, too.