#Quantum #Computers #Coming #Care
This video is brought to you by Skillshare. Quantum computers have been the stuff of science fiction for decades and promised by technology companies for almost as long. Although existing quantum computers can be computed on the fingers of one hand, their potential is absolutely massive.
These powerful machines could help us discover more efficient carbon capture materials, make the most out of renewable energy or find the perfect formula for our next generation batteries. In other words, quantum computing could solve the most pressing issue of our time: climate change.
So, when will quantum computers, with all their capabilities, begin to impact our real world? And will they really crack the code of our most puzzling enigma? Let’s see if we can come to a decision on this. I’m Matt Ferrell … welcome to Undecided.
In a recent video, I touched on how machine learning is being applied to improve renewable energy, which I’ll link to in the description. While looking into that, quantum computers kept coming up in our research. Solving the climate crisis and perfecting renewable energy and storage technologies is tricky.
Quantum computers are no longer science fiction and could be applied to help crack the code. The sci-fi nerd in me loves this. Before attempting to quantify the countless possibilities unleashed by quantum computers, we need to understand what they are and how they work. It’s kind of a mind trip.
To do this, we’ll have to run a superfast quantum physics class. Just kidding … I’m completely unqualified to do that and I don’t want to grind our brains down to a quantum. Anyway, at a very high level, quantum physics is the science studying quantum mechanics,
Which are the physical laws governing the behavior of subatomic particles like electrons, protons, neutrons, or photons. These are the physical objects that can be used as qubits, which are the smallest unit of data for quantum computers. While being an analog to “bits” used by traditional computers, qubits are a bit more sophisticated.
Now, there are two exotic properties that make qubits stand out. The first one is called superposition, meaning that, besides being binary and holding either 0s or 1s like a traditional computer bit, qubits can have both states at the same time. Like I said … this is a mind trip.
We have thought of bits like a coin flip, where it lands on heads or tails. With superposition, it’s like the coin stands on end and spins so that we can see heads and tails at the same time. To be more precise, a qubit’s superposed state is a linear combination of 0s and 1s.
This means that quantum computers can store and handle loads of information at once as they’re not bound to serial data processing like classical computers. To visualize the benefit of their parallel computations, just think of a postman lost in a maze with endless possible paths.
When remotely guided by a normal computer, he will have to go through one path at a time so it will take him ages to deliver his mail. Instead, if relying on a quantum machine, the postman can simultaneously check multiple ways out all at once.
Besides supercharged data handling, quantum computers can exponentially increase their information processing speed by leveraging qubits entanglement, which is their second exotic property. Entanglement is the process that links two or more qubits together. Once entangled, as you change the state of one qubit, the other ones will change as well
To solve problems that bits-based computers would take years to tackle. So, how do you make a physical qubit? Scientists have explored a bunch of options over the last few years. For instance, you could manipulate natural elements like the spin of an electron, which
Could be up or down, or both when you turn it into a qubit system. However, these can be hard to tweak and control given their miniature size. That’s why researchers have shifted towards man-made layouts, a.k.a. artificial atoms.
Out of all options available, etching a superconducting circuit on a microchip seems to be the most promising route to produce qubits on a large scale. Scientists have been working on superconductors and chips for decades. On top of that, this approach lets tiny particles work their magic…or quantum mechanisms if
You like…while designers play around with easy-to-handle hardware. Just a side note: One common type of superconductor is made of aluminum which can achieve practically zero resistance when cooled down below 1 degree K. These conditions make qubits more stable, which minimizes misleading measurements.
That’s called qubit decoherence, which can happen from environmental inputs like temperature changes or electrical resistance. By interconnecting multiple qubits, you can then build a Quantum Processing Unit (QPU), which is the quantum equivalent of a CPU. While standard machines’ processing power increases linearly with the number of transistors
You add, quantum computer capability rises exponentially as the number of qubits goes up. Which is why tech companies like Google and IBM have been trying to increase the number of qubits they can entangle together. Having said that, quality is better than quantity according to the former chief architect of
Google’s Sycamore, which achieved quantum supremacy for the first time in 2019. What he meant was that it’s better to build less fault-tolerant qubits than more error-prone ones, but more on that later. First we need to look at how quantum computers could freeze global warming.
But before we get to that … sometimes life can feel like quantum entanglement … I’m trying to find ways to disentangle my life, projects, and producing these videos, which is where Skillshare comes in. I’ve been on a roll with organization and productivity classes, and one of my favorites is from Thomas Frank (again).
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The first 1,000 people to use the link or my code undecidedwithmattferrell will get a 1 month free trial of Skillshare. Thanks to Skillshare, and to all of you, for supporting the channel. Now back to how quantum computers could freeze global warming. Clearly, by tapping into subatomic physics, quantum machines could make today’s supercomputers
Look like a Commodore 64. I’m having flashback to playing Super Huey as a kid. Anyway, while they would simplify a variety of once-intractable tasks, some research efforts are focusing on climate change mitigation, which is the top priority in our to-solve problem list.
Solar panels and wind turbines are the first weapons coming to mind when thinking about combating global warming, but they’ve got to be cost-effective. Choosing the best location for renewable facilities is key to minimize their start-up costs while maximizing their power generation.
Having said that, there are several parameters such as wind speed, distance from an accessible grid, wake effects etc. to factor in in the decision-making process. In this regard, researchers compared the performance of both a classical and a quantum processor when analyzing 14 facilities.
While the standard machine took over 11 hours to execute the calculations, the D-Wave quantum solver found an optimal spot for all facilities in only 16 minutes. Aside from supercharging clean power supply, we need to minimize our dirty energy demand. Quantum computers are more energy-efficient than ordinary machines.
And that’s mostly thanks to quantum tunneling. Due to a Josephson junction, which acts as an energy barrier that allows pairs of electrons, a.k.a. Cooper pairs, to hop from one electrode to the other. While this magic trick happens in a normal chip as well, in this case you’d need to
Apply much less voltage, which reduces power consumption by up to 100x. In addition, simulations jointly conducted by NASA, Google, and Oak Ridge National Lab found that a quantum machine required only 0.002% of the energy consumed by the world’s largest supercomputer to perform the same task.
When you think about the hardware used in data centers, which account for around 1% of global electricity use, replacing it with quantum devices would save us a huge amount of energy. While it sounds like a futuristic technology, you may see the impact of quantum computing on climate-friendly solutions earlier than you might expect.
According to BCG, qubits-based processors will enable the discovery of new environmental catalysts over the next 8 years. These could decarbonise some of our most carbon-intensive industrial processes. Relying on optimized algorithms, quantum machines can enhance computational chemistry through the faster processing power.
For instance, quantum computers could help lab scientists figure out how natural enzymes like nitrogenase can make bio-ammonia to manufacture fertilizers for crops. After years of work, a hybrid research team at the Pacific Northwest National Laboratory (PNNL) is getting very close to that goal. And that’s thanks to quantum chemistry simulations as well.
Nitrogenase can easily break down the nitrogen triple bond, which is the energy-greedy step in ammonia production. By replicating the nitrogenase trick, researchers could engineer synthetic catalysts yielding cheaper and greener ammonia. Once scaled up, these would let us ditch the Haber-Bosch reaction, which is the state-of-the-art process for making ammonia.
While being a well-established technique, the Haber-Bosch emits around 1.4% of global GHG emissions. Besides being used as an eco-fertilizer, green ammonia is a carbon-free fuel that could power ships or even heat our homes. By the onset of the next decade, error-corrected quantum machines will benefit material science as well.
For example, quantum computing could unleash more efficient materials for capturing CO2 from the air. That’s what Total had in mind when starting a collaboration with Cambridge Quantum Computing (CQC) in 2020. The energy giant is fine-tuning nanoporous materials to trap the carbon dioxide molecule into their cavities.
By developing new quantum algorithms and running simulations, CQC will evaluate materials’ capture performance based on pore size, shape and chemical composition, which would speed up Total’s selection process. As more households install solar panels on their roofs and charge EVs in the driveway, our electric grid is becoming more complex.
Optimizing this complex system will require enormous computing power, which is where quantum machines could…chip in. As part of their Vehicle to Grid (V2G) project, E.ON is connecting EV batteries into the distribution network. By functioning as flexible power storage, these units will balance out renewables fluctuations.
E.ON has allied with IBM to use their quantum tools to streamline this process. Speaking of batteries, IBM has also partnered with EV manufacturers to develop more sustainable chemistries compared to the state-of-the-art lithium-ion technology. For instance, Daimler AG is running quantum chemistry simulations to calculate the ground
State energy and the dipole moment of compounds typically produced during the operation of lithium-sulfur batteries. These parameters influence how the battery stores and discharges electricity. While traditional computers can simulate simple molecules, they still rely on lab experiments for more complex compounds.
In contrast, quantum computers enable a more precise and faster modeling of countless and complicated chemical compositions. This could accelerate Daimler efforts in fabricating the best recipe for next generation batteries. Since 2015, funding for start-ups in the quantum computing domain went from 0 to nearly $2 billion.
A speed worthy of a quantum machine I guess. This impressive growth in investments fueled the quantum race. As of last November, IBM led the way on superconducting qubits. That’s when the firm unveiled a 127-qubit machine based on the transmon architecture.
While this is a record for this type of technology, an MIT-backed start-up designed a 256-qubit neutral-atom quantum computer. Yet, on the heels of its Eagle machine, IBM is planning to fly high over the next few years. According to the firm’s quantum roadmap, they’ll have 1,121 qubits in their machines by 2023.
On the other hand, bundling as many qubits as possible in the same package is not enough. You’ve got to make sure they give you the right result. And that’s what Microsoft is working on. In terms of qubit error improvement, they’re qu-beating everyone else.
Last March, the software leader revealed a breakthrough in the development of topological qubits. Being more stable than other qubits, these elements could make quantum computations less error-prone. The company’s innovation stems from the practical application of Majorana zero modes. These are pairs of quasiparticles that are physically separated.
You could picture them as two half-electrons. As Majorana zero modes don’t interact with each other, encoding information onto them makes the qubit more tolerant to environmental perturbations, which avoids incorrect measurements. That sounds great, but there’s a catch. The physical existence of Majorana quasiparticles had never been proven to exist before … until now.
Following the theoretical setup, the Microsoft team wrapped a semiconducting nanowire in a superconducting layer and applied a magnetic field to it. After doing so, researchers measured some distinctive signals, called zero biased peaks, which confirmed the presence of Majorana zero modes at both ends of the nanowire.
While that’s a key milestone to achieve fault-tolerant quantum computers, we’ll likely get there by 2030. A lot of quantum computing is driven by this type of discovery- a particle is theorized to exist, the possibilities of its existence explored, and then it is proven to exist.
With regard to practical applications, Nvidia is betting on machine learning and quantum computing to develop more accurate climate models. If you saw my machine learning video, Nvidia has a lot going on. Last November, the semiconductor giant unveiled a supercomputer that could forecast the impacts
Of global warming on a meter-scale resolution across the entire planet. Basically, they developed a digital twin of Earth. By playing around with this virtual planet B the company will benefit the real world. Their climate models’ refined resolution would allow them to take into account local phenomena such as clouds reflecting sunlight.
One of their main innovations was the Fourier Neural Operator (FNO). This is basically a tutor for machines. By teaching physics to their computers their AI-aided models can then forecast natural disasters 100,000x faster than normal systems. On top of that, the firm is also investing in hybrid quantum computing to improve the
Accuracy of their predictions. In fact, chances are quantum computers won’t fully replace classical machines for some tasks. Rather, they could work together as an optimized hybrid system. For this purpose, the company is developing a new programming language to let regular and quantum machines speak to one another.
Wanting to ramp up hybrid quantum systems, Nvidia has also designed a tool for businesses that want to run quantum simulations for gaining climate science insights. Quantum computers are complex, weird and mighty systems that might give us a better shot at mitigating the effects of climate change.
Even though a lot of this is still at a start-up stage, their immense computational power could be part of the cure to our climate problem. With concepts like quantum entanglement this can be a bit hard to wrap your head around,
And it really does feel like something from science fiction (the geek in me loves that). However, with companies like Google, IBM, Microsoft, and Nvidia backing it up, we’re seeing that sci-fi fantasy become a reality. There’s still some debugging needed, but with the advancements over the past few years
There’s a huge amount of potential ahead of us. So are you still undecided? Do you think these kinds of advancements will help find solutions to climate change? Jump into the comments and let me know. If you liked this video, be sure to check out one of these videos over here.
And thanks to all of my patrons for your continued support and welcome to Jeff Back. And thanks to all of you for watching. I’ll see you in the next one.