When scientists want to do things like harness the power of molecules during photosynthesis, they won’t be able to do it using regular old computers. They need to use quantum computers, capable of measuring and observing quantum systems at the molecular level, as well as solving the conditional probability of events. Basically, quantum computers can perform billions of years of computation over the course of a weekend – and unravel some of the world’s most complex problems in the process.

**What is quantum computing?**

Quantum computing is a process that uses the laws of quantum mechanics to solve problems that are too large or complex for traditional computers. Quantum computers rely on qubits to run and solve multidimensional quantum algorithms.

In fact, quantum computing is very different from classical computing. Quantum physicist Shohini Ghose of Wilfrid Laurier University compared the difference between quantum and classical computing to light bulbs and candles: “The light bulb is not just a better candle; It’s something completely different.”

**Quantum Computing Explained**

Quantum computing solves mathematical problems and runs quantum models using the principles of quantum theory. Some of the quantum systems used to model include photosynthesis, superconductivity, and complex molecular formations.

To understand quantum computing and how it works, you first need to understand qubits, superposition, entanglement, and quantum interference.

**What are qubits?**

Quantum bits, or qubits, are the basic unit of information in quantum computing. Sort of like a traditional binary bit in traditional computing.

Qubits use superposition to be in multiple states at the same time. Binary bits can only represent 0 or 1. Qubits can be 0 or 1, as well as any part of 0 and 1 in the superposition of both states.

What are qubits made of? The answer depends on the architecture of quantum systems, as some require extremely low temperatures to function properly. Qubits can be made of trapped ions, photons, artificial or real atoms, or quasiparticles, while binary bits are usually silicon-based chips.

**What is superposition?**

To explain the superposition, some people evoke Schrödinger’s cat, while others point to the moments when a coin is in the air during the coin toss.

Simply put, quantum superposition is a mode in which quantum particles are a combination of all possible states. The particles continue to float and move as the quantum computer measures and observes each particle.

The most interesting fact about superposition — rather than the point of focus of two things at once — is the ability to observe quantum states in multiple ways and ask different questions, said John Donohue, science outreach manager at the University of California Institute of Technology. Waterloo Quantum Computing. That is, instead of executing tasks sequentially, like a traditional computer, quantum computers can perform a large number of parallel calculations.

This is as simplified as we can get before presenting equations. But the main conclusion is that this superposition is what allows a quantum computer to “try all paths at once”.

**What is input?**

Quantum particles are capable of corresponding measurements with each other, and when they are involved in this state, it is called entanglement. During entanglement, measurements of one qubit can be used to reach conclusions about other units. Entanglement helps quantum computers solve larger problems and compute larger stores of data and information.

**What is quantum interference?**

As qubits experience superposition, they can also naturally experience quantum interference. This interference is the probability of the qubits collapsing in one way or another. Due to the possibility of interference, quantum computers work to reduce it and ensure accurate results.

**How do quantum computers work?**

Quantum computers process information in a fundamentally different way than classical computers. Traditional computers operate on binary bits, but quantum computers transmit information through qubits. The qubit’s ability to remain in superposition is at the heart of the quantum’s potential for exponentially greater computational power.

Quantum computers use a variety of algorithms to perform measurements and observations. These algorithms are input by a user, the computer then creates a multidimensional space where patterns and individual data points are housed. For example, if a user wanted to solve a protein folding problem to find the least amount of energy to use, the quantum computer would measure the folding combinations; this combination is the answer to the problem.

The actual appearance of a quantum computer may vary. Technology companies such as IBM, Microsoft and Intel have developed quantum simulators and processors that can be accessed through purchases or special memberships. There are also a variety of open source quantum toolkits on the market that can be accessed online, such as through GitHub.

The physical construction of a true quantum computer mainly consists of three parts. The first part is a traditional computer and infrastructure that performs the programming and sends instructions to the qubits. The second part is a method for transferring signals from the computer to the qubits. Finally, there needs to be a storage unit for the qubits. This storage unit for qubits must be capable of stabilizing the qubits and certain needs or requirements must be met. They can range from needing to be close to zero degrees or housing a vacuum chamber.

It turns out that Qubits require more maintenance than even the most meltdown-prone rock stars. Any number of simple actions or variables can cause error-prone qubits to fall into decoherence or the loss of a quantum state. Things that can cause a quantum computer to fail include measuring qubits and performing operations. In other words: use it. Even small vibrations and temperature changes will also cause the qubits to pull apart.

This is why quantum computers are kept isolated, and those running on superconducting circuits – the most prominent method, favored by Google and IBM – have to be kept at near absolute zero (a cold -460 degrees Fahrenheit).

The challenge is twofold, according to Jonathan Carter, a scientist at Lawrence Berkeley National Laboratory. First, individual physical qubits need to have better fidelity. This could happen through better engineering, finding the ideal circuit layout, and the ideal combination of components. Second, we have to organize them to form logical qubits.

“Estimates range from hundreds to thousands to tens of thousands of physical qubits needed to form a fault-tolerant qubit. I think it’s safe to say that no technology we have right now could reach those levels,” Carter said.

From there, researchers would also have to build increasingly complex systems to handle the increase in qubit fidelity and numbers.

**What can quantum computing solve?**

Just as qubits can be in many states, the problems and challenges that quantum computing can solve are vast. There are several use cases for quantum computing: optimization, probability, molecular simulation, cryptography, and research.

Quantum computing can optimize problem solving by using QCs to run quantum-inspired algorithms. These optimizations can be applied to the fields of science and industry because they depend heavily on factors such as cost, quality and production time. With quantum computing, there will be new discoveries about how to manage air traffic control, package deliveries, energy storage and much more.

A breakthrough in quality control occurred in 2017, when IBM researchers modeled beryllium hydride, the largest molecule simulated on a quantum computer to date. Another important step occurred in 2019, when IonQ researchers used quantum computing to go even further, simulating a water molecule.

Generally, these problems are still small and can be verified using classical simulation methods. “But it’s moving toward things that will be difficult to verify without actually building a big particle physics experiment, which could get very expensive,” Donohue said.

“Most of the [commercial] interest comes from a long-term perspective. [Companies] are getting used to the technology so that when it catches up – and that timeline is a subject of fierce debate – they are ready for it.”

There is also hope that large-scale quantum computers will help speed up AI and vice versa – although experts disagree on this point. “The reason there is controversy is that things need to be redesigned in a quantum world,” said Rebecca Krauthamer, CEO of quantum computing consultancy Quantum Thought. “We can’t simply translate algorithms from normal computers to quantum computers because the rules are completely different, at the most elementary level.”

Some believe quantum computers could help combat climate change by improving carbon capture. Jeremy O’Brien, CEO of Palo Alto-based PsiQuantum, wrote that quantum simulation of larger molecules — if achieved — could help build a catalyst “to ‘clean’ carbon dioxide directly from the atmosphere.”

Quantum computers exist and are being used now. However, they are not currently “solving” climate change, boosting financial forecasting probabilities or performing other equally lofty tasks that are considered in reference to the potential of quantum computing. QC may have commercial applications related to these challenges, but that is still in the future.

Today, we are still in what is known as the NISQ – Noisy, Intermediate-Scale Quantum era. In short, quantum “noise” makes these computers incredibly difficult to stabilize. As such, NISQ computers cannot be trusted to make decisions of major commercial consequence, which means they are currently used primarily for research and education.

“The technology does not yet exist to provide a computational advantage over what could be done with other computing methods at this time,” Dohonue said. “Most of the [commercial] interest comes from a long-term perspective. [Companies] are getting used to the technology so that when it catches up – and that timeline is a subject of fierce debate – they are ready for it.”

But the R&D practicality of NISQ computers is demonstrable, albeit decidedly small-scale. Donohue cites the molecular modeling of lithium hydrogen. This is a small enough molecule that it can also be simulated using a supercomputer, but quantum simulation offers an important opportunity to “check our answers” after a classical computer simulation.

Generally, these problems are still small and can be verified using classical simulation methods. “But it’s moving toward things that will be difficult to verify without actually building a big particle physics experiment, which could get very expensive,” Donohue said.

And curious minds can get their hands dirty right now. Users can operate small-scale quantum processors via the cloud via IBM’s online Q Experience and its open source Quiskit software. Microsoft and Amazon now have similar platforms called Azure Quantum and Braket. “That’s one of the cool things about quantum computing today,” Krauthamer said. “We can all come in and play with it.”

**Why is quantum computing important?**

Quantum computers may have the potential to uproot some of our current systems. The cryptosystem known as RSA provides the security framework for a range of privacy and communications protocols, from email to Internet retail transactions. Current standards are based on the fact that no one has the computing power to test every possible way to decode your data once it’s encrypted, but a mature quantum computer could try every option in a matter of hours.

It should be emphasized that quantum computers have not yet reached this level of maturity – and won’t for some time – but if and when a large, stable device is built, their unprecedented ability to factor large numbers would essentially leave the RSA cryptographic system in disarray. rags. Fortunately, the technology is still a long way off – and the experts are on it.

*“The community feels pretty comfortable saying that’s not going to happen in the next five to 10 years.”*

“Don’t panic.” That’s what Mike Brown, CTO and co-founder of quantum-focused cryptography firm ISARA Corporation, advises eager potential clients. The threat is far from imminent. “What we hear from the academic community and from companies like IBM and Microsoft is that the 2026 to 2030 time frame is what we typically use from a planning standpoint in terms of systems readiness,” he said.

ISARA cryptographers are among several contingents currently participating in the Post-Quantum Cryptography Standardization project, a competition of quantum-resistant encryption schemes. The goal is to standardize algorithms that can resist attacks from large-scale quantum computers. The competition was launched in 2016 by the National Institute of Standards and Technology, a federal agency that helps establish technological and scientific guidelines, and is now preparing for its third round.

In fact, the level of complexity and stability required of a quantum computer to launch the much-discussed RSA attack is extreme. Even granting that deadlines in quantum computing – particularly in terms of scalability – are points of contention.

**The future of quantum computing**

Quantum computing may still be in its complicated and uncooperative phase, but that hasn’t stopped commercial interests from taking the plunge.

IBM announced at the Consumer Electronics Show that its so-called Q Network had expanded to more than 100 companies and organizations. Partners now range from Delta Air Lines to Anthem Health and Daimler AG, owner of Mercedes-Benz.

Some of these partnerships rely on the aforementioned promise of quantum computing in terms of molecular simulation. Daimler, for example, hopes that one day the technology will provide a way to produce better batteries for electric vehicles.

Elsewhere, partnerships between quantum computing startups and leading pharmaceutical companies – such as those established between 1QBit and Biogen, and ProteinQure and AstraZeneca – point to the drug discovery promise of quantum molecular modeling, however distant that remains.

Researchers would need millions of qubits to calculate “the chemical properties of a new substance,” noted theoretical physicist Sabine Hossenfelder in the Guardian. But the conceptual basis, at least, is there. “A quantum computer already knows quantum mechanics, so I can essentially program how another quantum system would work and use that to echo the other,” Donohue explained.

For people like Michael Biercuk, founder of quantum engineering software company Q-CTRL, “the only technical business milestone that matters now is the quantum advantage” – or, as he uses the term, when a quantum computer offers some timing advantage. or cost over a classic computer. Count him among the optimists: he foresees a period of five to eight years to achieve this goal.

Another open question: which quantum computing method will become standard? While superconduction has borne the most fruit so far, researchers are exploring alternative methods that involve trapped ions, quantum annealing or so-called topological qubits.

In Donohue’s opinion, it’s not necessarily about knowing which technology is better, but rather finding the best approach for different applications. For example, superconducting chips are a natural fit for the magnetic field technology that underpins neuroimaging.