Content:
Basics of quantum mechanics
Features of quantum computing systems
Quantum computing technology
Quantum software
Practical applications and use cases
The future of quantum computing
Conclusion
At the heart of today's digital infrastructure are classical computers. All devices, from smartphones to giant supercomputers, operate on the same fundamental principles established back in the middle of the 20th century. However, as scientific, technical, medical and industrial problems become more and more complex, we are increasingly pushing the limits of computing devices. Solving a number of complex problems is beyond the capabilities of even the most powerful classical computer.
This is where quantum computers, which use fundamentally new methods of computation based on the laws of quantum mechanics, come into play. They operate not with bits taking value 0 or 1, but with qubits capable to be in superposition state - simultaneously 0 and 1. Due to this quantum systems get possibility to process huge amount of data in parallel, expanding computing potential.
In this article we will understand the basics of quantum mechanics and its basic principles. We will find out what a quantum computer is, how it differs from a usual one, how it works and what tasks it is able to perform. Consider the challenges of quantum technologies and the prospects they open for mankind.
Quantum mechanics is a section of physics that studies the regularities of the behavior of particles and energy at the atomic and subatomic levels, which cannot be explained in terms of classical physics. One of the main differences in the microcosm: the states of particles can only be described by probability values. For example, one cannot know exactly where an electron is located, but one can describe the probability of it being in a certain region.
Quantum computing is based on the following concepts:
Superposition. A qubit can be in more than one state at a time until a measurement is made. This allows a quantum computer to process a huge number of choices in parallel.
Entanglement. There is an unbreakable entanglement between qubits, whereby a change in the state of one qubit affects the state of another, regardless of the distance between them. This property, which Einstein called "spooky long-range entanglement," allows complex correlations between qubits and multiplies the power of quantum computing structure.
Interference. Quantum states can reinforce or weaken each other, which is used in algorithms to increase the probability of a correct answer.
Decoherence. The interaction of qubits with the environment (heat, radiation, etc.) leads to loss of quantum properties, causing errors. Minimizing decoherence is one of the key challenges. Modern systems operate at 0.01 K (-273°C) in vacuum chambers to minimize external effects.
These principles are described in the National Academy of Sciences report, Quantum Computing Progress and Prospects:.
A qubit is the basic building block of quantum computing and can be physically realized based on any two-level quantum structure: for example, the spin of an electron, the polarization of a photon, the energy level of an atom (basic or excited), or the direction of current in a superconducting ring.
The quantum state of a qubit is described by a vector in a two-dimensional complex Hilbert space. Mathematically it is written as∣ ψ⟩=α∣ 0⟩+β∣ 1⟩, where∣ 0⟩ and∣ 1⟩ are ground states analogous to the classical 0 and 1; α and β are complex numbers called probability amplitudes. The squares of their moduli (∣ α∣ 2 and∣ β∣ 2) determine the probability of measuring a qubit in state 0 or 1, respectively. The condition∣ α 2+∣∣ β∣ 2=1 is always satisfied.
To use a simplified comparison of a qubit with a bit, a bit is a coin lying on the surface with eagle (0) or tails (1), and a qubit is a spinning coin where both states coexist and when the coin falls, with a certain probability the coin will be eagle or tails.
Until the moment of measurement the qubit is in superposition and all quantum information is "hidden" in the amplitudes. But as soon as we try to measure its state, it "collapses" to one of the classical values: |0⟩ with probability |α|^2 or |1⟩ with probability |β|^2.
The Bloch sphere provides a visual representation of the quantum state of a single qubit. The north pole represents the |1⟩ state, the south pole represents the |0⟩ state, and any point on the surface of the sphere represents a possible quantum superposition state.
The phenomena and regularities of the microcosm have formed the basis of the new generation of computing systems.
A quantum computer is a computing device that uses the phenomena of quantum mechanics, such as superposition and entanglement, to process and store information. The unit of information in classical computers is the bit, which is capable of being in one of two states: 1 (current flows through the transistor) or 0 (no current). In this case "value" and "state" are equivalent.
In quantum computers, the unit of information is the qubit, which also uses a binary code whose values can take 1 or 0, but whose range of states can vary infinitely between 0 or 1. As IBM notes, computational complexity grows exponentially as the number of qubits increases: 100 qubits can represent an astronomical number of states.
For comparison, the researchers sometimes bring up an ordinary light bulb that can be either off (state 0) or on (state 1) and a dimmer whose brightness can be infinitely adjusted, creating an infinite number of states between complete darkness (0) and bright light (1). In this case, the bit is analogous to an ordinary light bulb, for which there are only two states - on/off, and the qubit is the dimmer, which can take both the final values 0 and 1, and be in any intermediate state between them (i.e. be both 0 and 1 with a certain probability), thanks to the principle of superposition.
Manipulation of these quantum states opens up fundamentally different computational power to solve problems inaccessible to classical schemes.
The main difference between classical and quantum computers is the way they process information. Classical computers use bits that can be either 0 or 1, while quantum computers operate with qubits that can be in a superposition of states 0 and 1, which allows to perform many calculations simultaneously. Conventional structure process data sequentially, while quantum systems compute all possible options in parallel.
In addition, quantum computers utilize entanglement, in which qubits are linked in such a way that a change in the state of one instantly affects another, even over long distances. They apply quantum logic and interference to data processing, which makes them fundamentally different from classical structure that operate using deterministic algorithms.
Key differences between classical and quantum computing:
Characterization
Classical Computer
Quantum Computer
Unit of information
Bit (0 or 1)
Cubit (0, 1 or their superposition)
Relationship between units
Independence of bits from each other
Entanglement of qubits
Possible states
2 states: strictly 0 or 1
Infinite number of states
Principle of operation
Laws of classical physics and Boolean algebra.
Principles of quantum mechanics: superposition and entanglement.
Data processing
Sequential bit processing using logic gates (AND, OR, NOT). One operation per clock cycle.
Parallel processing due to superposition. Quantum gates affect all qubit states simultaneously (quantum parallelism).
Scaling
Increasing the number of qubits gives a linear increase in power.
Adding each new qubit doubles the computational space.
Scope of application
Wide range of tasks: from text editors to web servers.
Highly specialized, complex computations inaccessible for classical systems.
Resistance to errors
High. Bits are stable
Low. Quantum states are unstable and affected by the environment (decoherence).
Power consumption
High
Ultra-low (cryogenic environments)
Classical computers have relatively simple architecture (motherboard, processor, memory cards, etc.), work in natural conditions, have affordable cost and are suitable for everyday professional and personal use (work with texts, graphics and video, Internet search, etc.).
Quantum computers have a complex structure, require the creation of special environments (due to the instability of qubits) and the use of expensive technologies. They are designed to solve complex specific problems, such as molecular modeling, factorization of large numbers, optimization of complex systems, search in disordered databases, etc.
Classical and quantum computers are not competitors, but rather tools for different tasks. It is unlikely that a quantum computer will ever replace your laptop on which you work with documents or watch movies. The purpose of quantum computers is to solve tasks that are inaccessible for conventional computing structure.
Let's look at the logic of quantum computing and the basic algorithms by which quantum computers work, understand their components.
Gates are commonly referred to as logic elements that convert input states of bits/qubits to output states according to a certain law.
Just as classical computers use AND, OR and NOT operators to perform operations on bits, quantum computers convert qubits through some fundamental operations that can affect their quantum state (quantum gates).
Some basic quantum gates are:
Adamar's valve (H) - creates a superposition. If you apply it to a qubit in the state∣ 0⟩, it will move to a state where the probabilities of getting 0 or 1 are equal.
Pauli gates (X, Y, Z) are analogs of the classical NOT gate, but for different axes on the Bloch sphere. They change∣ 0⟩ to∣ 1⟩ and vice versa.
The CNOT (Controlled-NOT) valve is a two-qubit valve required to create entanglement. It inverts the second (target) cubit only if the first (control) cubit is in the state∣ 1⟩.
T, S are additive complex phases. Important for the versatility of the set of gates.
By combining these and other gates, one can construct any quantum circuit and hence realize any quantum algorithm.
The operation of a quantum computer is based on quantum algorithms that utilize the quantum properties of particles to speed up computation.
Examples of quantum algorithms:
Shor's algorithm - factorizes (decomposes into prime factors) large numbers in polynomial time. Poses a serious threat to RSA cryptosystems based on factorization.
Grover's algorithm - speeds up searches in unordered databases by a factor of √n (with quadratic acceleration). It is used to optimize logistics and other processes.
Quantum simulation - allows modeling of quantum systems. It is used in chemistry, physics, materials science, astronomy and a number of other fields.
Recently, American scientist Odeda Regev proposed a new algorithm that potentially outperforms Shor's algorithm (Wevolver) due to the multidimensional geometry techniques used in lattice cryptography. He generalized Shor's approach by extending it to an arbitrary number of dimensions (only two dimensions in the original algorithm), which optimized quantum operations and improved computational efficiency.
Creation of quantum software is a process of development and implementation of algorithms using quantum programming languages (Q# from Microsoft, Quantum from IBM) and special libraries for Python (for example, Qiskit, Cirq, PennyLane, PyQuil).
Quantum programs are designed to perform computational tasks on devices that use quantum phenomena for data transmission and processing. Their creation is one of the basic tasks in the field of quantum technologies.
Example: Quantum Computing Playground is a web application that runs Grover and Shor algorithms. It contains an environment for writing, compiling and executing code, as well as ready-made example algorithms.
Moving from the theoretical principles of quantum mechanics to creating a working device is an enormous engineering challenge that requires innovative solutions and sophisticated hardware. Various technologies are used to create qubits, each with its own advantages and limitations. Their choice depends on specific tasks and scalability.
The heart of any computer is its processor. Unlike silicon processors of classical computers, there are no unified standards for quantum processors yet. Different companies and research groups are experimenting with different physical systems to create qubits. The main approaches are:
Superconducting qubits - microscopic-sized circuits with superconducting properties in which current can flow in two directions simultaneously (superposition). Requires extremely low temperatures close to absolute zero (about -273 °C) to suppress thermal noise. Such circuits behave like artificial atoms in a cryogenic environment; their strengths are fast gates and potential for scaling. An example: the IBM Quantum system is the Eagle processor with 127 qubits or the Osprey with 433.
Ion trap qubits - holding individual ions (charged atoms) in a vacuum using electromagnetic fields or a laser. Encoding of quantum states in this case occurs in the energy levels of ions. Such qubits are more stable (have a longer coherence time) and can keep their quantum state longer, provide high accuracy of gates and natural coupling between ions through their oscillations. But they are more difficult to scale and operations with them are slower. IonQ and Honeywell are working with ion technology.
Photonic qubits - with a photon (a particle of light) as the carrier of quantum information. The photon's ability to polarize is used for encoding. Photons interact weakly with their surroundings and do not require cryogenic temperatures. The problem is the difficulty of creating a deterministic interaction between photons. Research in this area is being conducted by the Canadian company Xanadu Quantum Technologies.
Topological qubits - based on exotic quasiparticles (Majorana fermions) whose states are more robust to external noise. Potentially more reliable, but are in the early stages of research (Microsoft et al.).
Quantum dots - charge states of electron and nuclear spin. Semiconductor nanocrystals are used, ranging in size from 2 to 10 nanometers. Rigetti Computing, IonQ
Regardless of the platform, the main tasks of the hardware are to initialize qubits, perform precise operations on them and read out the final result while protecting the quantum system from external influences. For example, IBM Quantum uses superconducting circuits to create qubits where current flows in two directions simultaneously.
Leading companies are actively developing quantum processors. IBM introduced the Eagle processor with 127 qubits in 2021 and plans to release Kookaburra with 1,386 qubits in 2025, which can be combined into a system with 4,158 qubits.
Microsoft announced Majorana 1, an eight-cubit topology processor that is considered more error-resistant.
These advances show progress in building scalable quantum systems.
One of the major challenges to building a large-scale quantum computer is decoherence (loss of a quantum state). Quantum states are unstable and any random interaction with the environment (vibration, electromagnetic field, temperature change) can break the superposition or entanglement and introduce errors into the computation.
The solution to this problem is quantum error correction (QEC). The idea is similar to classical error correction: the information of one logical qubit is encoded using multiple physical qubits. By detecting and correcting errors on the physical qubits without destroying their logical state, the integrity of the information can be maintained.
Surface codes are currently the most promising approach to QEC. A logical qubit is encoded into a topological structure (grid) of many physical qubits (tens or hundreds per logical qubit). Stability is ensured by the topological properties of the mesh. This approach allows error detection and correction, but requires many physical qubits for one logical one.
The ultimate goal of the developers: a quantum structure equipped with QEC, where errors at the physical level are effectively suppressed, allowing any long and complex computations to be performed on logical qubits. But building such a computer requires a huge number of high-quality physical qubits and sophisticated control.
So far we are at the intermediate stage of Noisy Intermediate-Scale Quantum noisy(NISQ) "" quantum devices. They do not yet have full correction, which limits their application.
IBM plans to introduce advanced error correction techniques by 2029, which will enable fault-tolerant quantum computers.
Although quantum computing is still at an early stage of development, there are already visible areas where it could revolutionize.
Possible applications include:
Pharmaceuticals and medicine. Radically accelerate the development of more effective and safer drugs - by accurately simulating in quantum systems the interaction of drugs with proteins
Materials Science. Creating new materials with tailored properties (e.g., high-temperature superconductors or more efficient catalysts for industry).
Financial modeling. Optimization of investment portfolios, more accurate assessment of risk, pricing and complex financial instruments.
Artificial intelligence and machine learning. Accelerating the training of AI models, solving complex optimization problems, finding patterns in huge datasets.
Process optimization. Solving logistical, production and other problems, the complexity of which grows exponentially with the number of variables.
Cryptography. Development of quantum-resistant algorithms.
It is expected that quantum systems will gradually learn to cope with any problems, from solving supercomplex scientific tasks to creating secure networks resistant to hacking and hacker attacks.
It is worth mentioning separately the use of quantum technologies in the field of communications. Quantum algorithms have created a threat to cryptography, but they can also find a solution - to develop algorithms that are resistant to hacking by quantum computers.
Quantum key distribution (QKD) protocols already allow creating secure communication channels. Their security is based on a fundamental law of quantum physics: any attempt to intercept and measure quantum information will inevitably alter it, which will be immediately noticed by legitimate users.
Quantum Key Distribution technology uses entanglement or the uncertainty principle to detect interception. It enables secure data exchange, but requires a dedicated fiber optic or free-beam infrastructure to implement.
QKD is currently already in practical use by ID Quantique and Toshiba. The research aims to create a secure quantum internet that will connect quantum devices around the world.
Quantum computers can solve tasks much faster than classical computers. The CPU of classical computers is based on transistors, where all bits are independent and changing one of them does not affect the state of another. And qubits in quantum systems are bound by entanglement - changing one of them instantly affects the other, even at a distance. For any number of N qubits, 2 to the degree of N states are created. That is why quantum computers are characterized by high performance and perform operations thousands of times faster, which makes them in demand for scientific and industrial tasks.
They can perform such operations as molecular modeling, cryptanalysis, factorization (Shor's algorithm), search in disordered systems (Grover's algorithm), etc. in a short time. They can be used to accelerate training of AI models, select parameters of neural networks and develop fundamentally new ML approaches.
Example. In 2019, the Sycamore quantum computer based on a 54-qubit processor created by Google performed in 200 seconds a task that would have taken 10 thousand years for the most powerful modern Summit supercomputer.
A few examples of practical use of quantum technologies:
Modeling complex chemical reactions inaccessible to classical systems (IBM).
Google modeled a hydrogen molecule (2016), IBM modeled beryllium hydride (2017).
VisionQuest Enterprise Group optimized portfolios and reduced risk through quant algorithms.
A quantum network established in China in 2020 used entanglement to realize "unhackable" communication.
Quantum computing is undergoing rapid development. For example, IBM plans to achieve quantum advantage by 2026 and create a fault-tolerant Starling computer by 2029. Microsoft is experimenting with topological qubits, which promise high stability.
Research in quantum technologies is active around the world: in academia, research departments of technology giants (IBM Quantum, Google, Microsoft) and startups.
Quantum systems have enormous potential, but face great challenges in practical implementation.
The main challenges in quantum computing are:
Qubit scaling - increasing the number of physical qubits while maintaining their quality (coherence time, gate precision, etc.). Millions of qubits are required to create fault-tolerant systems, which is impossible to realize in practice.
The quality of qubits is to increase coherence time and accuracy of operations. It is necessary to develop hardware with lower noise level, capable to resist decoherence phenomenon.
Quantum error correction - realization of efficient QEC codes in practice, which will require a huge number of physical qubits per one logical one (redundancy factor).
Coupling of qubits into a single architecture - development of efficient ways to connect many qubits to each other in large processors, which is technologically very difficult to do.
Quantum software - development of new efficient quantum algorithms for fault-tolerant machines is needed.
Active work is underway to increase the number of stable high-quality qubits. For example, IBM plans to create a 1000-qubit chip by 2030.
There are also plans to integrate quantum and classical computers. In such hybrid systems, quantum computers will play the role of gas pedals, balancing accuracy and speed of operations.
The benefits of quantum computing lie not in simply increasing the speed of operations, but in a radically different way of processing information, which opens up a huge potential for the development of quantum technologies. By using quantum states of entanglement and superposition, it is possible to solve many complex problems that are unattainable for classical computers even theoretically. Therefore, quantum advantage is not a myth, but a concrete goal to which the industry is moving at an accelerated pace.
Problems that seem insoluble today will be solved with the help of quantum technologies, leading to scientific breakthroughs, creation of new industries and improvement of the quality of life. We are on the threshold of a new technological revolution, comparable in scale to the discovery of electricity or the invention of the conventional computer.
McKinsey estimates that the opportunities presented by quantum technologies could create a market worth up to $2 trillion by 2035.
Quantum technologies through accurate modeling can help to better understand the fundamental laws of physics, solve the most complex mathematical problems, get a more accurate picture of the state of the early universe. With their help it is possible to create new materials with specified properties and super-efficient medicines, to optimize global systems of power grids, transport flows and logistics chains, to develop quantum-resistant cryptography, to reduce resource and financial costs, to reduce the ecological footprint. Through quantum systems it is also possible to accelerate machine learning and create fundamentally new, more powerful forms of artificial intelligence.
Quantum computing is a technology that promises revolutionary breakthroughs in science, technology and industry. They open new horizons in many fields, from molecule modeling to the optimization of complex systems. Despite a number of major challenges, there is active work going on in the field of quantum computing, with research progress being made by companies such as IBM and Microsoft, for example. It is expected that in the coming years quantum technologies will be significantly improved and we will be closer to the creation of a full-fledged quantum computer.