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 Is Quantum Computing?

Indeed, quantum computing is vastly different from classical computing. Quantum physicist Shohini Ghose, of Wilfrid Laurier University, has likened the difference between quantum and classical computing to light bulbs and candles: “The light bulb isn’t just a better candle; it’s something completely different.”

## What Is Quantum Computing?

Quantum computing solves mathematical problems and runs quantum models using the tenets of quantum theory. Some of the quantum systems it is 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 one 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 superposition of both states.

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

**WHAT IS SUPERPOSITION?**

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

Put simply, quantum superposition is a mode when quantum particles are a combination of all possible states. The particles continue to fluctuate and move while the quantum computer measures and observes each particle.

The more interesting fact about superposition — rather than the two-things-at-once point of focus — is the ability to look at quantum states in multiple ways, and ask it different questions, said John Donohue, scientific outreach manager at the University of Waterloo’s Institute for Quantum Computing. That is, rather than having to perform tasks sequentially, like a traditional computer, quantum computers can run vast numbers of parallel computations.

That’s about as simplified as we can get before trotting out equations. But the top-line takeaway is that that superposition is what lets a quantum computer “try all paths at once.”

**WHAT IS ENTANGLEMENT?**

Quantum particles are able to correspond measurements with one another, and when they are engaged in this state, it’s called entanglement. During entanglement, measurements from one qubit can be used to reach conclusions about other units. Entanglement helps quantum computers solve larger problems and calculate bigger 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 qubits collapsing one way or another. Because of the possibility of interference, quantum computers work to reduce it and ensure accurate results.

## How Do Quantum Computers Work?

### They Use Qubits and Computational Algorithms

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

Quantum computers use a variety of algorithms to conduct 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 wants to solve a protein folding problem to discover the least amount of energy to use, the quantum computer would measure the combinations of folds; this combination is the answer to the problem.

### They Rely on Quantum-Specific Computer Infrastructure

The physical build of a true quantum computer consists mainly of three parts. The first part is a traditional computer and infrastructure that runs programming and sends instructions to the qubits. The second part is a method to transfer 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 able to stabilize the qubits and certain needs or requirements have to be met. These can range from needing to be near zero degrees or the housing of a vacuum chamber.

### They Require Physical Isolation and Cooling Mechanisms

Qubits, it turns out, are higher maintenance than even the most meltdown-prone rock star. Any number of simple actions or variables can send error-prone qubits falling into decoherence, or the loss of a quantum state. Things that can cause a quantum computer to crash include measuring qubits and running operations. In other words: using it. Even small vibrations and temperature shifts will cause qubits to decohere, too.

That’s why quantum computers are kept isolated, and the ones that run on superconducting circuits — the most prominent method, favored by Google and IBM — have to be kept at near-absolute zero (a cool -460 degrees Fahrenheit).

## What Can Quantum Computing Solve?

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

### Molecular Modeling and Simulations

One quantum computing breakthrough came in 2017, when researchers at IBM modeled beryllium hydride, the largest molecule simulated on a quantum computer to date. Another key step arrived in 2019, when IonQ researchers used quantum computing to go bigger still, by simulating a water molecule.

### Climate and Energy Optimization Problems

Some believe quantum computers can 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 “for ‘scrubbing’ carbon dioxide directly from the atmosphere.”

### Artificial Intelligence Breakthroughs

There’s also hope that large-scale quantum computers will help accelerate artificial intelligence technologies, and vice versa — although experts disagree on this point. “The reason there’s controversy is, things have to be redesigned in a quantum world,” said Rebecca Krauthamer, CEO of quantum computing consultancy Quantum Thought. “We can’t just translate [AI] algorithms from regular computers to quantum computers because the rules are completely different, at the most elemental level.”

## Quantum Computing Challenges

### Quantum Noise Disruptions

Currently, we’re still in what’s known as the NISQ era — Noisy, Intermediate-Scale Quantum. Quantum noise refers to any disturbances that affect the state of qubits, which can disrupt superposition, entanglement and the overall accuracy of quantum systems. This noise can be caused by multiple factors like temperature, electromagnetic or mechanical fluctuations, making quantum computers incredibly difficult to keep in a proper quantum state. As such, NISQ computers can’t be trusted to make decisions of major commercial consequence, which means they’re currently used primarily for research and education.

### Quantum Technology Is Difficult to Scale and Actualize

While quantum computing has the potential to solve complex problems, its operational output and level of qubits required to actually complete these tasks are demanding, and the technology has yet to scale to be able to support these needs.

With qubits in particular, the challenge is two-fold, according to Jonathan Carter, a scientist at Lawrence Berkeley National Laboratory. First, individual physical qubits need to have better fidelity. That would conceivably happen either through better engineering, discovering optimal circuit layout, and finding the optimal combination of components. Second, we have to arrange them to form logical qubits.

“Estimates range from hundreds to thousands to tens of thousands of physical qubits required to form one fault-tolerant qubit. I think it’s safe to say that none of the technology we have at the moment could scale out to those levels,” Carter said.

For example, researchers would need millions of qubits alone to compute “the chemical properties of a novel substance,” noted theoretical physicist Sabine Hossenfelder in the Guardian. Plus, the fragility of large-scale quantum systems make it difficult for current technologies to properly stabilize them long enough to even function.

But the conceptual underpinning, at least, is there to overcome these hurdles. “A quantum computer knows quantum mechanics already, so I can essentially program in how another quantum system would work and use that to echo the other one,” explained Donohue.

Additionally, the challenges that quantum computing faces aren’t strictly hardware-related. The “magic” of quantum computing also resides in algorithmic advances, “not speed,” Greg Kuperberg, a mathematician at the University of California at Davis, is quick to underscore.

“If you come up with a new algorithm, for a question that it fits, things can be exponentially faster,” he said, using exponential literally, not metaphorically.

### Quantum Computing Standards Are Still Being Developed

Another open question: Which method of quantum computing will become standard? While superconducting 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 view, it’s not necessarily a question of which technology is better so much as one of finding the best approach for different applications. For instance, superconducting chips naturally dovetail with the magnetic field technology that underpins neuroimaging.

### Lack of Quantum Computing Expertise

One roadblock for quantum computing, according to Krauthamer, is general lack of expertise. “There’s just not enough people working at the software level or at the algorithmic level in the field,” she said. Tech entrepreneur Jack Hidarity’s team set out to count the number of people working in quantum computing and found only about 800 to 850 people, according to Krauthamer. “That’s a bigger problem to focus on, even more than the hardware,” she said. “Because the people will [need to] bring that innovation.”

## Why Quantum Computing Is Important

### Quantum Computers Can Review Classical Computer Results

Quantum computers’ research and development practicality is demonstrable, if decidedly small-scale. Donohue cites the molecular modeling of lithium hydrogen. 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.

These are generally still small problems that can be checked using classical simulation methods. “But it’s building toward things that will be difficult to check without actually building a large particle physics experiment, which can get very expensive,” Donohue said.

### Quantum Computing May Transform Cryptography

Quantum computers may have the potential to uproot some of our current systems. The cryptosystem known as RSA provides the safety structure for a host of privacy and communication protocols, from email to internet retail transactions. Current standards rely on the fact that no one has the computing power to test every possible way to de-scramble your data once encrypted, but a mature quantum computer could try every option within a matter of hours.

It should be stressed that quantum computers haven’t yet hit that level of maturity — and won’t for some time — but if and when a large, stable device is built its unprecedented ability to factor large numbers would essentially leave the RSA cryptosystem in tatters. Thankfully, the technology is still a ways away — and the experts are on it.

“Don’t panic.” That’s what Mike Brown, CTO and co-founder of quantum-focused cryptography company ISARA Corporation, advises anxious prospective clients. The threat is far from imminent. “What we hear from the academic community and from companies like IBM and Microsoft is that a 2026-to-2030 timeframe is what we typically use from a planning perspective in terms of getting systems ready,” he said.

Cryptographers from ISARA are among several contingents that have taken part in the Post-Quantum Cryptography Standardization project, a contest of quantum-resistant encryption schemes. The aim is to standardize algorithms that can resist attacks levied by large-scale quantum computers. The competition was launched in 2016 by the National Institute of Standards and Technology, a federal agency that helps establish tech and science guidelines, and is now gearing up for its third round.

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

## The Future of Quantum Computing

Quantum computers do exist, and they are being used right now. They are not, however, presently “solving” climate change, turbocharging financial forecasting probabilities or performing other similarly lofty tasks that get bandied about in reference to quantum computing’s potential. Quantum computing may have commercial applications related to those challenges, but that’s well down the road.

“The technology just isn’t quite there yet to provide a computational advantage over what could be done with other methods of computation at the moment,” said Dohonue. “Most [commercial] interest is from a long-term perspective. [Companies] are getting used to the technology so that when it does catch up — and that timeline is a subject of fierce debate — they’re ready for it.”

Though quantum computing still has a ways to go before a wide-scale commercial debut, curious minds can still get their hands dirty with the technology today. Users can operate small-scale quantum processors via the cloud through IBM’s online Q Experience and its open-source software Quiskit. Microsoft and Amazon both now have similar platforms, dubbed Azure Quantum and Amazon Braket. There are also over 60 algorithms listed and over 400 papers cited at Quantum Algorithm Zoo, an online catalog of quantum algorithms compiled by Microsoft quantum researcher Stephen Jordan. “That’s one of the cool things about quantum computing today,” said Krauthamer. “We can all get on and play with it.”

## Frequently Asked Questions

### What is quantum computing in simple terms?

Quantum computing refers to computing that operates off of the laws of quantum mechanics in order to solve problems faster than classical computers. Quantum computers use qubits to have information be in multiple states (such as 0 and 1) at once.

### What can quantum computers do?

Quantum computers can run quantum algorithms to accelerate problem-solving processes. These processes may be applied to areas in medical research, financial modeling, AI and more to make decisions with increased accuracy and speed.

### Do quantum computers exist now?

Quantum computers exist now, though they are mainly used in data centers, laboratories and universities for research and education purposes.

### What is the main goal of quantum computing?

Quantum computing aims to speed up research and development initiatives as well as solve complex data or optimization problems that classical computers are unable to process.