Quantum computing is a type of computing technology that employs principles of quantum mechanics such as superposition, entanglement, and interference.
It can process, store, and manipulate large quantities of data, perform complex calculations, and even run conventional computing systems.
This article will explain quantum computing’s importance and its applications.
Quantum computing is a type of computing that employs quantum mechanics principles such as superposition, entanglement, and interference.
It can process, store, and manipulate large amounts of data, perform complex calculations, and even compete with supercomputers.
The chips used to compute bits are the basis of today’s computers. These bits can take one or zero values, where one is the ‘on position’ and zero is the ‘off position.’
Many of these bits reveal a combination number of ones and zeroes, the basic units of any website, app, or photograph we access or use.
Bits are helpful, but they don’t reveal the true nature of our universe beyond what is happening at the moment. Our world is characterized by uncertainty. However, even supercomputers can’t process uncertainty, creating a computing vacuum.
Scientists discovered over the past century that sub-atomic physical laws are not applicable and distinct from those we see daily. This led to the uncertainty factor.
Quantum mechanics was born, which helped decode subatomic elements’ science. This was the foundation of physics, biology, and chemistry.
Technologists now needed a way to manage uncertainty while performing calculations. Quantum computing was born.
It is based upon physical laws that govern the subatomic world, where elementary particles can simultaneously exist in multiple states and places.
It observes the behavior of matter and energy at the quantum level and uses it to create a quantum computing model.
Quantum computing technology thus uses, manipulates, and controls quantum theory laws to perform complex tasks and computations with some uncertainty.
Although quantum computing technology is still relatively new, companies like IBM, Google, and D-Wave are making significant progress.
IBM made a giant leap forward in quantum computing by announcing its first commercially available quantum computer.
On the other hand, Google announced in October 2019 that it had created a quantum machine capable of solving a complex problem in just 200 seconds.
This is a significant leap in quantum computing, and it would have taken 10,000 years to build the fastest supercomputer in the world.
What is quantum computing?
Binary systems are used to encode data on computers today. This binary framework is run on processors that use transistors to compute.
The transistors are switches in the computer’s circuitry and create 0s or 1s to process computation logic. Quantum computers, however, have these 0s or 1s replaced by quantum bits (also known as qubits), which encode quantum information and process different quantum states.
The following are critical components of the quantum computing model:
Quantum computers are based on qubits. These are quantum-mechanical systems that can accept different quantum values and scale exponentially above the conventional ones or zeros.
A two-qubit system, for example, can do four concurrent computations, while a three-qubit system can do eight. A four-qubit system, on the other hand, can do 16.
Let’s take a look at the qubit representation.
The aforementioned figure demonstrates that a bit can hold values of 0, 1, and 2. The sphere representation shows, on the other hand, that the qubit may take up multiple values identified at the sphere’s surface.
Each point is associated with a subsequent pair of latitude and longitude, representing 0 or 1, respectively.
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Superposition means that the quantum system can be in multiple states simultaneously. For example, consider a coin-toss scenario. The coin ends up being either heads or tails when it is flipped.
If we look at the coin’s state when it is suspended in air, it can hold both heads and tails simultaneously. Quantum particles, such as electrons, are also in quantum superposition until measured.
In quantum computers, this ‘uncertainty factor is eliminated.
Entanglement is tying two or more qubits together and establishing a relationship between them. Entangled qubits mean that any change to one qubit will immediately impact the other.
Let’s take, for example, the addition of a qubit to a 60-qubit computing device. The quantum computer can simultaneously evaluate 260 states in such a situation.
The computer can perform faster computations by adding a qubit to the entanglement property. Hence, quantum computing algorithms use quantum entanglement for faster data processing.
Interference is a technique for manipulating the quantum states of a quantum machine. It involves strengthening or decreasing the wave functions of quantum particles.
In this way, the output of quantum states that produce a correct result can be amplified, and those that do not can be canceled.
Quantum machines perform poorly in noisy environments. External noise can cause quantum devices to fail. This is because the qubits”superposition state’ disrupts their computations, leading to errors.
Quantum states also retain information for a short time. Therefore, you must perform analyses while the data is still alive, as quantum states can lose coherence quickly.
Quantum computers are kept at shallow temperatures to overcome these problems. Because heat is susceptible to noise and errors, it is preferable to maintain quantum computers at lower temperatures to enable qubits to retain more extended quantum states, including superposition and entanglement.
Let’s look at an example to show how the quantum computer works.
Suppose you invite five people to your wedding and need to plan their seating arrangements. There are five ways to do this. = 120.
A conventional computing system will evaluate each of these 120 options, compare them, and finally decide on the optimal solution.
A quantum computer, however, takes the following steps to optimize seat allocation:
Considers qubits and creates quantum superpositions for all possible quantum states.
The encoder assigns phases to each quantum state and configures qubits. The amplitudes for possible sitting ways in phase add up, while the amplitudes for out-of-phase paths cancel out.
This is similar to noise cancellation technology found in headphones and speakers, where noise is created to eliminate external noise.
The quantum computer uses interference to cancel out or increase some answers. The quantum computer finally finds a single solution to optimize seat allocation.
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Why Quantum Computing is essential
Quantum computing is expected to transform many industries, including finance, medicine, machine learning, and cryptography.
Governments, investors, and businesses that want to achieve total quantum supremacy are the main drivers of quantum computing advancements.
The ‘National Quantum Initiative’ was launched by the U.S. government in 2019. It seeks to expand the field of quantum computing. The government also provided $1.2 billion to promote the quantum realm.
Conversely, China is investing $10 billion to build the ‘National Laboratory for Quantum Information Sciences.
Quantum computing is becoming more accurate, so it is essential to grasp its significance.
Benefits of Interference in Quantum Computing
Interference in quantum computing refers to the phenomenon where multiple quantum systems can affect each other, leading to a loss of coherence and decreased computational accuracy. However, this same phenomenon can also be harnessed to provide benefits for certain quantum algorithms.
For example, in quantum algorithms based on the principles of quantum interference, such as the quantum Fourier transform, the interference between quantum states can be used to extract information and solve computational problems faster than classical algorithms.
In addition, quantum interference can also be used for error correction in quantum computing, which is important for building scalable, practical quantum computers.
By exploiting the interference between different quantum states, it is possible to detect and correct errors in the quantum data, which helps to increase the accuracy and reliability of quantum computations.
Overall, interference in quantum computing can hinder or aid computational accuracy and efficiency, depending on how it is utilized in a particular algorithm or application.
Nevertheless, the benefits of quantum computing, such as exponential speedup over classical algorithms, make it a promising area of research and development.
#1. The search for solutions to complex, rising problems
Earthlings face more complex problems than advanced technology can solve. These complex problems are so complicated that it would take decades for supercomputers to resolve them.
Modern cybersecurity problems, optimization, stock profile management, and problems related to aerospace, molecular studies, and other issues are just a few examples.
Another example is protein modeling. The scientific community needed help finding a tool to deactivate and model a single protein within a shorter timeframe during the COVID-19 pandemic.
This tool could have saved the world’s health from this crisis. Energy usage is another crucial area. The world’s population has seen an exponential increase in energy consumption.
This has led to the problem of energy source optimization, which is very difficult for computers today. Quantum computing is finally making it possible to solve complex problems.
#2. Quantum computing has excellent commercial potential
Let’s look at an example of an app that benefits farmers, agricultural companies, and allied industries. It’s well known that approximately 50% of the world’s food production depends on ammonia fertilizers.
This chemical process, called the “Haber-Bosch Process,” produces ammonia at high temperatures and pressures. It is difficult to overcome the physical limitations of this process, as they result in significant energy consumption.
This is one of the biggest problems. Quantum computers are here to help. An enzyme called “nitrogenase” can produce ammonia fertilizer at standard temperature and pressure. This enzyme is created using a complex catalytic process that computers today cannot understand.
This involves molecular modeling, where nitrogenase can be mapped by traversing nearly 1,000 carbon atoms. It reduces industrial production of nitrogenase and affects overall industrial output for ammonia-based fertilizers.
Quantum computers can help by creating molecular models for nitrogenase. Computing can also design similar molecules to the enzyme and produce low-cost, low-energy ammonia.
Quantum computing would make ammonia-based fertilizers readily available at affordable prices. This technology could also lower the energy consumption commonly associated with nitrogenase production.
#3. Nonlinear problems supported
Classical computing best suits linear problems where sequential operations are the main focus. These computing systems are based on linear mathematics, which studies transformation properties and linear equations.
Nature is fundamentally nonlinear, with some uncertainty. Traditional methods cannot solve these nonlinear problems. Quantum computers are capable of processing nonlinear data.
Traffic equilibrium optimization, the probability of a moon landing, and others are examples of nonlinear problems.
#4. The handling of a massive increase in data
We live in the digital age, where vast amounts of data are generated daily. Every IoT device, wearable gadget, sensor, and gadget connected to a computing network contributes to data generation.
Domo estimates that computing devices produce 2.5 million bytes of data per day. Computers and supercomputers can make errors when handling large amounts of data. This can affect performance.
Classic computers cannot handle complex computational tasks, such as testing drugs’ effects on the molecular level.
Quantum computers, on the other hand, are better suited to such jobs because they can process large volumes of data much faster.
Top 8 Applications of Quantum Computing
Quantum computing has created opportunities in many industries and disciplines.
These include pharmaceuticals, chemical engineering, information and communication technology, finance, automotive, and aerospace. Let’s look at eight of the most critical applications that quantum computing has created.
#1. Machine learning
Quantum computing can fine-tune machine learning algorithms, such as neural networks.
Quantum computing can also be used to optimize popular machine learning and deep learning algorithms widely used in optimization. They combine quantum and classical simulations to solve problems.
Quantum computing is capable of processing large amounts of data and can help in making better decisions. This includes applications like facial recognition, object recognition, and fraud detection.
Quantum computing-inspired computer learning can be used to design methods to counter cybersecurity threats. It can also be used to develop encryption techniques and drive the quantum cryptography industry.
#2. Drug development
Quantum computing is a critical component of drug development. Drugs can be tested for stable molecular configurations using molecular modeling processes.
Quantum computers can run advanced simulations on different organic molecules, which help determine the suitability of the drug.
Combinatorial optimization problems can be solved using quantum computing when the specific molecules required for drug development are unknown or not available.
Simulator-based trials are a great way to quickly get drugs on the market and save money on research and development.
#3. Model chemical processes
Quantum computing is a critical component in the design of molecular structures. This includes the nitrogenase enzyme found in ammonia-based fertilizers.
Quantum-based simulations can model chemical processes as well as complex atomic interactions. They can also speed up lab experimentation, which uses trial and error. Quantum computing could revolutionize chemical engineering.
Quantum computing can overcome the shortcomings of traditional algorithms, which are slow in processing time-sensitive financial transactions.
Quantum computing can manage stock portfolios, invest in, and trade financial securities. Let’s take an example of a high-frequency trading model.
These models have a significant time lag between two consecutive financial transactions. This time lag can cause investors to suffer losses as they cannot rebalance frequently.
Quantum computing can solve this problem by speeding up the financial calculations involved in trading. Banks can also use quantum computing to optimize portfolios, schedule financial transactions, and prioritize them.
Quantum computing can be harnessed through quantum processors. These processors combine multiple qubits with quantum properties to provide the best answer.
Quantum computing can also determine financial risks by speeding up Monte Carlo simulations. It develops models that use probability distributions for uncertain variables and yields possible results.
It can calculate multiple results using different probabilities and values.
#5. Aircraft development
Companies can use quantum computing to design aircraft. It is possible to model and digitize the entire plane, allowing faster simulation.
Aerospace engineers spend a lot of time modeling the flow of air currents above the aircraft wings. This can take months or years. Quantum computing can perform faster mathematical calculations, improving aircraft design efficiency.
They can also apply quantum principles to other purposes, such as optimizing fuel usage and controlling the aircraft’s speed. This will help meet the sustainability goals of the industry.
#6. Automotive industry
The quantum computing paradigm is already being used in the automotive industry. Volkswagen, an industry leader, has teamed up with D-Wave, a quantum computing provider, to jump into the quantum-enabled future.
A few Volkswagen buses were equipped with D-Wave’s navigation app, which offers real-time quantum services such as congestion data and the best destination routes.
This is down to milliseconds. In Jan 2020, Mercedes-Benz Group (Daimler AG) partnered with IBM to develop next-generation lithium battery technology with a quantum computer.
#7. Climate models are being developed
The climate models used today to forecast weather should be more accurate. Simulating real-world conditions requires several inputs. Classical computing systems are unable to handle large amounts of data input.
Quantum computers can take as much information as they want, which can help develop accurate climate models. Quantum computers can simulate minor environmental variables, such as wind, temperature, and humidity, and understand how they react to changing weather conditions.
Researchers can track and calculate many environmental parameters in real-time, which could help with weather prediction.
#8. Solid material development
Researchers can use quantum computing to create quantum-mechanical simulations that help determine the properties and characteristics of advanced materials.
Quantum Monte Carlo can be used to model the internal structure of solid materials, which allows for the discovery of new materials that are much more difficult to compute with conventional computing models.
In 2020, for example, IBM’s 53-qubit Hummingbird quantum computer was used by researchers at the University of Chicago to create a new quantum material called ‘exciton condensation’ through quantum simulations.
Quantum computing is still very young. Quantum computing is still in its infancy. The current quantum computers have particular requirements for hardware and cooling temperatures.
Quantum computing will soon be a standard computational technology as large corporations, governments, and academic institutions continue investing millions in quantum computing research and development.