Quantum computers are not supposed to check your emails, update your status, or do normal software/hardware tasks. Instead, they are designed to perform complicated tasks such as financial modeling, climate modeling, material discovery, supply chain optimization, machine learning Acceleration, and much more.
Unlike conventional computers that employ a binary number system, quantum machines are based on something more complicated – Quantum Mechanics.
They deal with particles much smaller than the size of atoms. At such smaller scales, the usual rules of physics do not make any sense. This is where exciting things begin to happen. Particles could move back and forth or can even exist simultaneously.
Machines that leverage quantum particles (to process information) can significantly increase computational power beyond what is achievable by today’s conventional computers.
Let’s elaborate on what we know about quantum computing at present. We’ve gathered some interesting facts about quantum computers that will truly captivate your imagination.
Table of Contents
1. Information storage pattern: Qubits
The computers we use today store data in a binary format – a series of 0’s and 1’s. Each component of memory is called a bit, and it can be manipulated via steps of Boolean logic.
On the other hand, a quantum computer stores data as either a ‘0’, ‘1’, or a quantum superposition of the two states. Such a quantum bit (also known as Qubits) has far greater flexibility than a binary system.
Qubits could be implemented using particles with two spin states – “up
2. Qubits can exist in multiple states simultaneously
Since data in quantum computers can exist in more than just 0’s and 1’s states, they can perform calculations in parallel.
Take a simple example: if a qubit is in a superposition of states 0 and 1 and performs a calculation with another qubit in a similar superposition, it would yield four outcomes – 0/1, 0/0, 1/0, and 1/1. These outcomes are visible when the quantum computer is in a state of decoherence, maintaining a superposition until it collapses to a single state.
This capability to do multiple tasks at once is called quantum parallelism.
3. Unbreakable security features
The speed of quantum computers raises concerns in encryption and cryptography. Current financial security relies on factoring large numbers (RSA or DSA algorithms), which traditional computers can’t crack within Earth’s lifespan. Quantum computers, however, could factor these numbers relatively quickly.
The plus point is quantum machines can also offer unbreakable security features. They can use stronger encryptions to safeguard crucial data like online transactions and email accounts.
Numerous algorithms have been developed for quantum computers. The most popular ones are Grover’s algorithm (for searching an unstructured database) and Shor’s algorithm (for factoring large numbers).
4. Extremely Power Efficient
Large arrays of processors demand a substantial power supply to maintain their performance. For instance, the fastest supercomputer in the world (Frontier) consumes as much as 70 megawatts.
Quantum computers, however, bring an intriguing twist. By harnessing quantum tunneling, they have the potential to slash power consumption by a factor of 100 to 1000.
5. Impressive Computation Speeds
According to quantum physics, we deal with something called Multiverse, where a problem may have many or infinite probable solutions. For example, as you read this article on your laptop, in another universe, you might be reading it on your mobile while traveling.
A quantum computer can tackle ‘n’ tasks across ‘n’ parallel universes to reach an outcome. While a traditional computer performs ‘n’ calculations in ‘n’ seconds, a quantum computer can execute ‘n²’ calculations in the same time frame.
Consider IBM’s Deep Blue, the first computer to defeat world chess champion Garry Kasparov in 1997 by analyzing 200 million possible moves per second—a feat beyond human brain capacity. If it were a quantum machine, it could have computed 1 trillion moves per second, 4 trillion moves in 2 seconds, and 9 trillion moves in 3 seconds
6. The challenges of stability and decoherence
Quantum computers face a challenge with stability. It turns out the interference (any kind of vibration upsets the vibration of atoms) creates gibberish output.
In quantum mechanics, electrons act like waves and are defined by a wavefunction. When these waves interfere, it triggers peculiar quantum particle behavior known as decoherence.
This interference can arise due to various factors, such as vibrations, temperature fluctuations, and electromagnetic radiation. When qubits lose their coherence, it leads to errors in computations.
7. Near Zero Temperature for Optimal Performance
For optimal performance and stability, a very low temperature is required to keep quantum computers running smoothly. To maintain atom stability, the most effective technique is reducing the temperature to near zero Kelvin, where atoms remain stable without releasing heat.
One of the most advanced supercomputers is the D-Wave 2000Q system. Its superconducting processor is cooled to 0.015 Kelvin (180 times colder than interstellar space).
8. Solve certain problems faster
Quantum computers can execute classical algorithms, but their real power lies in leveraging algorithms that tap into inherently quantum features, such as quantum entanglement or superposition (for more efficient results).
While undecidable class problems remain unsolvable in quantum computing, what makes quantum algorithms fascinating is their ability to solve certain problems faster than classical algorithms. For example, they can crack the traveling salesman problem in seconds, a task that takes 30 minutes on conventional computers.
Furthermore, quantum computers can help discover distant planets, forecast weather precisely, detect cancer earlier, and develop more effective drugs by analyzing DNA sequencing data.
9. AI Game Changer
Artificial intelligence is still in its early stages. Although advanced robots today can enter a room and recognize materials, shapes, and moving objects, they lack the elements that truly make them intelligent.
Quantum computers, on the other hand, excel in information processing—with just 300 bits, we could map the entire universe.
In the field of machine learning, quantum computers have the potential to accelerate operations exponentially, reducing processing time from hundreds of thousands of years to mere seconds.
For example, measuring the distance between two large vectors of 1 Zettabyte size — a conventional computer with a GHz clock rate would take hundreds of thousands of years. In contrast, a future GHz clock rate quantum computer, if built, would accomplish this task in just a second after entangling the vectors with an ancillary qubit.
10. Not Everything Can Be Made Fast
Quantum computers excel at finding the most optimal solutions to problems, yet they rely on the same fundamental mathematical principles that personal computers use every day. This involves basic arithmetic that is already well-optimized.
For tasks like adding a set of numbers, the most effective method is simply adding them up. In such cases, classical computers are just as efficient as quantum computers.
11. Data in a quantum state cannot be copied
Data encoded in a quantum state exhibits a unique characteristic: it cannot be copied. Any attempt to read this data will alter its quantum state. This feature can be leveraged to detect eavesdropping in quantum key distribution.
More specifically, this feature offers a huge advantage in quantum communication for establishing secure cryptographic keys. It underscores the unique security properties offered by quantum systems for certain cryptographic tasks.
12. Quantum Neural Networks
These networks leverage the principles of quantum mechanics to perform specific computations more efficiently than classical neural networks. They are made of quantum neurons and quantum gates, analogous to classical neurons and gates in classical neural networks.
Their architecture can be defined using quantum circuits that evolve over time as the network learns and adapts to different tasks.
These networks have the potential to significantly enhance machine learning tasks, such as pattern recognition, optimization, and classification.
13. Simulate Quantum Machines
“In an ion trap quantum simulator with 51 particles, the scientists have imitated a real material by recreating it particle by particle and studying it in a controlled laboratory environment”
https://t.co/vDQKpWAhP8— Fluidityinglass (@Fluidityinglass) November 30, 2023
One of the most important applications of quantum computing is quantum simulators. They allow the analysis of quantum systems that are impossible to model with supercomputers and difficult to study in the laboratory.
These simulators are specifically designed to provide insight into certain physics problems. They can be built using conventionally programmable ‘digital’ quantum computers, capable of solving a wide array of quantum problems.
So far, quantum simulators have been realized in many different experimental platforms, including systems of trapped ions, polar molecules, ultracold quantum gases, quantum dots, and superconducting circuits.
14. Programming Language For Quantum Computers
In 2020, researchers introduced Sliq, an easy-to-understand high-level programming language for quantum computers.
Quantum computation often poses challenges for developers. They have to deal with several frustrating things, such as a low level of abstraction that leads to cluttered code, temporary values that need to be discarded, and much more.
While some quantum languages attempt to address these issues, they often do so in a complex manner. In contrast, Sliq supports safe, automatic uncomputation, offering an intuitive semantics.
Other notable imperative quantum programming language
- Quantum Computation Language (QCL) supports the representation of quantum gates, quantum data types, and operations, which are the building blocks of quantum algorithms.
- Logic of Quantum Programs (LQP) is a dynamic quantum logic that effectively captures essential aspects of quantum measurements and unitary evolutions of multi-partite states.
- Q# is developed by Microsoft to be used in the Quantum Development Kit. It incorporates a set of functions and operations for representing quantum information, such as qubits and quantum registers.
- Ket plays an important role in Ket Quantum Programming Platform, seamlessly integrating with a Rust runtime library and a quantum simulator. It is an open-source embedded language developed and maintained by Quantuloop.
15. Companies at the forefront of quantum computing research
Major props to @GuidoAndEscanor for pointing this out—
Quantum Computers seem to resemble the inverted Tower of Babel
There are between 150–200 Quantum Computers worldwide (Google, IBM, CERN)— all are built the same
So not only can you see the Tower of Babel resemblance in pic.twitter.com/NnkdcKmUkb
— Truechucknorris (@snjegi333) December 2, 2023
Several companies are investing heavily in quantum computing research, each making significant contributions to advancing the field. The most popular names include:
IBM has developed and deployed a series of quantum machines. IBM Condor chip, in particular, represented a significant leap in qubit count. It’s a 1,121 superconducting qubit quantum processor based on our cross-resonance gate technology. They have also developed an open-source quantum software development framework called Qiskit.
Google’s Quantum AI Lab gained significant attention when they demonstrated quantum supremacy using the Sycamore processor. This 53-qubit processor can perform specific tasks more efficiently than the most advanced classical computers. They also experimentally explore topologically ordered quantum states and techniques for reducing quantum errors.
Microsoft has developed Q# programming language for expressing quantum algorithms, Quantum Development Kit for simulating and debugging quantum programs, and fault-tolerant quantum processors for practical applications in areas such as optimization, chemistry, and machine learning.
Honeywell Quantum Solutions focuses on a trapped ion quantum computing architecture. In this approach, individual ions are trapped and manipulated using electromagnetic fields to represent qubits. They have developed a series of trapped-ion quantum processors that offer improved qubit connectivity and error correction.
D-Wave is known for its quantum annealing approach. Their quantum processors are designed to solve real-world problems, especially those related to protein design, resource scheduling, traffic routing, and financial modeling.
16. David Deutsch pioneered the field of quantum computation
Quantum computing was first mentioned by Richard Feynman in 1959 in his famous lecture ‘There is plenty of room at the bottom.’ In this lecture, he explored the idea of manipulating individual atoms as an advanced form of synthetic chemistry.
In 1981, David Deutsch formulated the concept of a quantum Turing machine, establishing the theoretical groundwork for quantum computation. He proposed a universal quantum computer in his 1985 paper titled “Quantum Theory, the Church-Turing Principle and the universal quantum computer.”
17. The first quantum key distribution protocol
The world’s first quantum key distribution protocol, BB84, was developed by IBM researchers Gilles Brassard and Charles Bennett in 1984. It’s a technique of securely sending a private key from one point to another for use in one-time pad encryption.
The BB84 protocol utilizes the principles of quantum mechanics to detect any eavesdropping attempts. It laid the foundation for the field of quantum key distribution, which ensures the security of communication in a quantum environment.
18. Quantum algorithms
A realistic model of quantum computation runs on quantum algorithms, which can be classified based on the type of problem they solve or the techniques and ideas they employ. Presently, there are algorithms rooted in amplitude amplification, quantum Fourier transform, and hybrid quantum algorithms.
This is an active area of research, and developers are continually exploring new algorithms and applications for quantum machines. As quantum hardware and error correction methods improve, the scope and feasibility of quantum algorithms for solving practical problems are expected to expand.
19. Physical implementations of quantum machines
There are various physical implementations being explored for quantum computers. The most popular ones are
- Superconducting and trapped-ion quantum computer
- Spin-based and spatial-based quantum dot
- Diamond-based quantum computer
- Cavity quantum electrodynamics
- Molecular magnet quantum computer
Each of these physical implementations has its own set of benefits and challenges. Notably, superconducting and trapped-ion systems have demonstrated promising results. Tech giants like IBM and Google have made significant strides in constructing and scaling quantum processors based on these technologies.
20. Quantum computing market will reach $6.5 billion by 2033
According to Future Market Insights, the global quantum computing market size will reach $6.5 billion by 2033, growing at an impressive CAGR of 23.5%.
The key factors behind this growth include advances in quantum hardware (such as the development of more stable qubits and improved coherence times), the emergence of quantum cloud services, and significant investments from governments and private companies.
Furthermore, the increasing focus on quantum education and workforce development programs is nurturing a new generation of developers with expertise in quantum information science.
21. Significant Achievement In Quantum Computing
21.A
In 2015, Scientists at the University of New South Wales developed the first quantum logic gate using silicon. In the same year, NASA revealed the first operational quantum computer made by D-Wave worth $15 million.
21.B
In 2016, researchers at the University of Maryland successfully created the first reprogrammable quantum computer. Two months later, Basel University specified a variant of the electron-hole-based quantum machine that uses electron holes (instead of manipulating electron spins) in a semiconductor at low temperatures, which are quite less vulnerable to decoherence.
21.C
In 2018, the Quantum Artificial Intelligence Lab (run by the Universities Space Research Association, NASA, and Google) released a 72-qubit processor named Bristlecone.
21.D
In 2019, Google AI, in partnership with NASA, published a paper claiming that they have achieved quantum supremacy — a breakthrough in the history of quantum computing.
21.E
In 2020, a team of researchers at the University of California, Los Angeles, set a new record for preparing and measuring quantum bits inside a quantum computer without error. More specifically, they achieved a preparation and measurement error rate of 0.03%. It will impact almost every area of quantum information science.
21.F
In 2021, researchers at Stanford and Princeton University used Google’s quantum computer to demonstrate a genuine “time crystal,” a novel state of matter that breaks the conventional rule of time-translation symmetry.
21.G
In 2022, researchers simulated a theoretical wormhole using a quantum system. The experiment serves as a valuable testbed for exploring concepts related to quantum gravity physics using a quantum computer.
21.H
In 2023, IBM revealed the first quantum computer boasting over 1,000 qubits. The company now aims to focus on improving error resistance rather than increasing the size of these machines.
“It’s a machine unlike anything we have ever built,” says Dario Gil, the head of research at IBM. 60 Minutes got a first look at IBM’s newest quantum computer, its most advanced to date. https://t.co/9WBYVtZUgQ pic.twitter.com/BrJDncaalX
— 60 Minutes (@60Minutes) December 4, 2023
More to Know
Major challenges in the quantum computing industry
The quantum computing industry faces numerous challenges that span software, hardware, and theoretical aspects. The major ones are:
- Decoherence, which refers to the loss of quantum information due to external interactions
- Quantum machines are susceptible to errors caused by noise and imperfections in hardware
- As the number of qubits increases, maintaining coherence and reducing errors become exponentially more difficult
- Ensuring qubits can interact with each other in large-scale machines is an ongoing challenge
- Several current quantum technologies, such as superconducting qubits, require extremely low temperatures to operate
Are quantum computers accessible to the general public?
At present, quantum computers are primarily developed and managed by leading tech companies and research laboratories. Tech giants like Google, IBM, and Microsoft allow people to access and experiment with quantum machines remotely through the internet.
You can use these cloud-based services to run quantum algorithms, test your code, and gain hands-on experience with quantum computing. Some companies even provide quantum development kits and software tools, allowing researchers and developers to write and simulate quantum programs.
Can quantum computers coexist with classical computers?
Yes. In fact, there exists a concept of a hybrid quantum-classical computing model. In this model, quantum processors work in conjunction with classical processors to execute tasks more efficiently than either could alone.
It allows us to harness the potential advantages of quantum machines for specific tasks while maintaining the reliability of classical computers for more general applications. This coexistence is considered a transitional phase until a fully fault-tolerant quantum machine becomes available for broader use.
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