# The next step vital to solve climate change: finding the next-gen batteries

On the road to addressing climate change, one vital step is increasing the capacity to store energy, particularly through batteries. If we hope to transition into renewable energy sources for the majority of our needs, we must find are able to find the batteries “for tomorrow”. We have been using lithium-ion batteries since 1991, and there have not been any significant changes since. We are currently approaching the limitations of these batteries and we are going to need a new plan for the transition to renewable energy. Well, how can we do that, what technology do we need? Many scientists are already solving this problem with **quantum computers, **and this is not the only problem quantum computers can solve**. **To understand what quantum computers are and how they can solve such problems, we need to understand the history, the physics and the technology utilized for quantum computing.

The story of quantum computing dates to back to when quantum physics was first discovered. The fundamental mathematics — quantum mechanics — of quantum physics was discovered in the 1920’s and proved the positions and change particles had over time. They were developed by Niels Bohr, Werner Heisenberg, Erwin Schrödinger, and others; however, this was only the first step of the tough long journey. Scientists needed to connect quantum mechanics to other areas of physics, mainly Einstein’s theory of relativity, to be applied to the real world.

You may have heard of the famous 1930’s Bohr–Einstein debates where Albert Einstein and Niels Bohr debated on the concept of quantum physics. Bohr argued quantum physics was real, while Einstein argued that quantum physics was inconsistent and quoted it as “spooky action at a distance”. Einstein’s main concern was that entanglement between particles forced the “communication” to be faster than the speed of light, which cannot be true. Einstein later published an EPR or statement in 1934 stating that there was a missing deeper meaning about quantum physics. Soon the connection to the theory of relativity came from John Bell in 1964 who figured out how to test the EPR statement. He stated that entanglement was a whole new phenomenon and named it “nonlocal”.

Before we go into how these findings were used for quantum computing, let’s dive deeper into the physics. Quantum theory deals with the behaviour of energy and matter at the atomic and subatomic scale. There are three different quantum field theories and they deal with the three fundamental forces of how matter interacts: electromagnetism, the strong nuclear force and, the weak nuclear forces. While everything in quantum physics is important, the fundamental principles — **superposition** and **entanglement — **are the most crucial aspects of quantum computing. Let’s look at a simplified version of the famous Schrödinger cat thought experiment to understand superposition and entanglement — originally the experiment was explained all through one box. Imagine a box with a cat and a bomb that has a 50% chance of blowing up: the box and cat represent a particle. Until we open the box there is absolutely no way we can know whether the bomb has exploded or not. Now, this is where superposition and entanglement come into play. Before our observation the cats were in a superposition state, meaning that the cats were neither dead nor alive but rather with a 50% chance for each. In reality, physics at the quantum scale, superposition looks quite similar. For example how the electron orbiting in a hydrogen atom does not orbit, but rather is kind of everywhere in space with higher probabilities of being in certain areas. We can only know for sure its place at a certain time if we measure its position. This connects back to the cat analogy, without opening the box, we cannot know if the cat is dead or alive. But about entanglement? Well, now think of two boxes rather than one that is in an entangled state. Now we have four possible outcomes and by simple probability, we can say that each outcome has a 25% chance:

- (box 1) dead & (box 2) dead
- (box 1) alive & (box 2) dead
- (box 1) dead & (box 2) alive
- (box 1) alive & (box 2) alive

Here’s the catch, because of entanglement we can eliminate options (1) and (4). Through quantum mechanics, we can figure out that one cat will always be dead and the other alive, even if the two boxes are put across the universe. Furthermore, we cannot determine the outcome until we open a box. Recall that John Bell called this “communication” nonlocal because nothing can be faster than light, this “communication” had to be its own phenomenon. When two subatomic particles are entangled and put in a superposition state in the real world, one will spin one way and the other has to spin the other way. Once we open a box, we can measure the states of the two cats; or in real life, we can measure the state of a particle to measure it.

The theory of quantum physics was soon put to the test in 1959 when Richard Feynmon suggested that when electronic components reach microscopic scales, it can be used to create powerful computers by using quantum physics — this entails that when something reaches the atomic and subatomic scale it can manipulate things like superposition and entanglement. He wanted to harness the power of superposition and entanglement since we already know what this looks like both scientifically and figuratively, let’s learn about how it can be manipulated to create a quantum computer.

In classical computers we have binary digits — these are called bits — and they can have the number 0 or 1 — these numbers hold information when put together. Hence if there were 4 bits, the computer would hold **one **of 24 possible numbers. However, in a quantum computer, we would have qubits and these work a little differently. Each of the qubits would be in superposition, and as mentioned earlier this means that the qubit has the value of both 0 and 1; instead of holding 1 out of the 16 possible numbers, it would hold **all** 16 simultaneously. It is also important to note that the computing power increases exponentially as the qubits increase; hence, having 40 fully functional qubits would overpower the world’s fastest supercomputers. This allows a quantum computer to outperform a classical computer when more qubits are added.

Quantum computers work more efficiently by having qubits with a probability of being 0 or 1 instead of a “decided” state — so you can think of it almost being both. The state of the qubit can be described to have an arbitrary point on a sphere, refer to Figure 1. This picture is the Bloch sphere representation and it describes what a qubit state could be. The |0⟩ and |1⟩ show the point a classical bit can access, while a qubit point can be anywhere on the equator of the sphere, hence the probability factor.

A quantum computer can do the math on the qubit even if it is in superposition — this occurs by logic gates, which are carefully calibrated light pulses. Using these logic gates,** **a result of either 0 or 1 can be obtained. Here is where entanglement plays its part. When the qubits are entangled, they affect each other instantly when measured; you can think of this like every qubit is connected.** **Hence, when given a problem, instead of needing to carry a long list of sequential steps like in classical computers, all of the qubits can be “read” altogether. This solution is then outputted by **interference. **Interference is similar to how noise-cancelling headphones work… they provide the opposite wavelengths (the opposite sounds). Quantum computers manipulate interference properties allowing the “right answer” to be amplified and the “wrong answers” to be canceled. This works together to allow quantum computers to give the output almost instantly.

*Side Note*

*The equation for a qubit is ∣ψ⟩ = α∣0⟩ + β∣1⟩*

*This equation describes a qubit’s probability of being either 0 or 1. Let’s break it down. ∣ψ⟩ represents the qubit, and α and β in the equation represent the complex probability amplitude. The complex probability amplitude is essentially just the probability of being either 0 or; hence, how the equation represents the probability of a qubit being the value 0 or 1.*

Now that we know how quantum computers would work in theory, let’s explore real life applications. The quantum computers are these chandelier-like machines, refer to Figure 2. It is made of copper tubes, wires, and a core that contains a superconducting chip. The superconducting chip is where the qubits are arranged in a chessboard-type pattern. To understand why the superconducting chip is made in a specific manner, we have to understand classical computers and the way they compare to quantum computers. A classical computer works like this, each bit is stored on a capacitor on a dynamic ram or DRAM which is like a board that holds tons of bits on it. A charge = 1, no charge = 0 and the charge is actually decided by over 300,00 electrons! What this means is that each bit has electrons. think of it as being inside a box. Once all of the electrons move out of the “box” its value becomes zero and when holding electrons the value becomes 1. The thing with electrons is that they move around, and sometimes escape randomly because of their low mass; hence, if there were only a few electrons and they escaped, it would be an error (which is why there are so many). Furthermore, there is a safety guard: the DRAM circuit occasionally checks and replenishes any missing electrons. If this is how a bit worked on a classical computer, it would be logical to think a quantum computer would be the same thing, except with qubits that are in superposition.** **Here’s the catch, it simply would not work because of the rule that when a qubit is in superposition and is observed, it automatically collapses into one of the values, 0 or 1––the key is to make the logic gates reversible. This is not the only problem quantum computers deal with. Another way a qubit in superposition collapses is if it comes across any light interference. One way scientists tackle these problems is by cooling down the circuit metals — aluminum — to super-low temperatures of below 1º Kelvin. This allows the electrons to join together in a single unit instead of thousands and hence the rate of quantum errors drops significantly. As shown in Figure 2, there are different “levels’’ in a quantum computer with a quantum chip or superconducting chip at the lowest level. The lower the level, the colder the temperature. Most of the cables send light pulses to the qubit and can entangle qubits, put them into superposition and measure them through logic gates.

One major problem quantum computers are facing today is how sensitive qubits are and become “nonsense” quickly. Many scientists are working to create a computer that can run without creating any decoherence; thus, making a more reliable computer. While quantum computing will take years, if not decades to make a “perfect” quantum computer, once it is made it will help take huge leaps in almost every sector such as medicine, and chemistry. Currently, the largest quantum computer is 65 qubits; however, it is unstable, it uses qubits that are not fully functional and easily decoherence. Even if scientists add more qubits, they also need to lower the error rate, or as seen in Figure 3, the computing volume will not increase.

Let’s go back to how quantum computers can find “the batteries of the future”. Quantum computers can handle algorithms that would take a classical computer a very long time, and they can handle algorithms created to design batteries with greater capacity and replicate the chemistry needed to create the next-gen batteries. This is the first step to creating a world free from emissions, but it is a crucial step to reduce the impacts of climate change.

*References*

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