What is Quantum Computing? Latest Breakthroughs in 2025

Quantum computing is projected to become a $1.3 trillion industry by 2035 . We’ve seen remarkable progress in this field, especially after Google AI and NASA announced their achievement of quantum supremacy with a 54-qubit machine in 2019, performing calculations impossible for classical computers .

What is quantum computing? At its core, quantum computing harnesses the laws of quantum mechanics to perform certain calculations exponentially faster than today’s most powerful supercomputers . However, current hardware implementations remain largely experimental and suitable only for specialized tasks . Despite these limitations, researchers expect quantum computers to excel at calculating properties of physical systems that are inherently quantum mechanical .

Recently, researchers at the University of Sydney Nano Institute have demonstrated a significant breakthrough – quantum logic gates that require far fewer physical qubits to function, thus increasing their efficiency . This development represents an important step forward in making quantum computing more practical.

In this article, we’ll explain how quantum computing works, explore the fundamental concepts like qubits and entanglement, examine the latest breakthroughs of 2025, and discuss real-world applications that might transform industries from pharmaceuticals to cybersecurity.

What is Quantum Computing? A Simple Explanation

Image Source: Alamy

“We couldn’t build quantum computers unless the universe were quantum and computing. We can build such machines because the universe is storing and processing information in the quantum realm. When we build quantum computers, we’re hijacking that underlying computation in order to make it do things we want: little and/or/not calculations. We’re hacking into the universe.” — Seth Lloyd, Professor of Mechanical Engineering and Physics, MIT; quantum computing pioneer

Unlike classical computers that surround us daily, quantum computers operate according to the strange, counterintuitive laws of quantum mechanics [[1]](https://scienceexchange.caltech.edu/topics/quantum-science-explained/quantum-superposition). These machines harness quantum physics—the fundamental principles governing the universe at its smallest scales—to process information in revolutionary ways [[2]](https://quantum.cloud.ibm.com/learning/courses/quantum-business-foundations/quantum-computing-fundamentals). How does quantum computing work in theory?

Quantum computing differs fundamentally from conventional computing through its use of instead of classical bits quantum bits or “qubits”[2]. While classical bits represent either 0 or 1, qubits can exist in multiple states simultaneously thanks to a phenomenon called superposition [3]. This property allows quantum computers to process an exponential number of possibilities at once [4].

For example, two classical bits contain just two pieces of information (like 00, 01, 10, or 11), whereas two qubits can represent all four combinations simultaneously [2]. This capability scales exponentially—three qubits can represent eight combinations, four qubits sixteen combinations, and so on [1].

Another crucial quantum principle is entanglement, where quantum particles become linked in such a way that their states are dependent on each other regardless of distance [5]. When qubits become entangled, changes to one qubit directly affect others, enabling parallel processing and boosting computational power [6].

Additionally, quantum systems utilize quantum interference, which helps amplify correct answers while suppressing incorrect ones [1]. Together, these principles give quantum computers their extraordinary processing abilities for specific types of problems.

What is a quantum computer with example use cases?

A quantum computer is a device that takes input data and transforms it according to quantum operations, typically represented by quantum circuits [7]. Various technologies are being developed to build quantum computers, including:

Trapped ion systems that use charged atoms suspended by electromagnetic fields [7]
Superconducting circuits operating at cryogenic temperatures [7]
Photonic processors that manipulate light for computations [7]
Neutral atom systems using light to trap uncharged atoms [7]

Quantum computers won’t replace classical machines but instead complement them for specific applications [7]. Real-world use cases include:

Drug discovery and materials science – Quantum computers can simulate molecular interactions at the quantum level, potentially accelerating pharmaceutical research [2][7]
Financial modeling – They can optimize investment portfolios and assess risks more effectively by processing complex market variables [7]
Cryptography – Quantum computers could break traditional encryption but also enable more secure communication through quantum cryptography [7]
Optimization problems – Supply chain logistics, traffic flow, and energy grid management can benefit from quantum algorithms that efficiently explore solution spaces [7]

Difference between classical and quantum computing

Classical and quantum computers differ in three primary ways [6]:

First, their basic units of information contrast sharply. Classical computers use bits—familiar 0s and 1s—while quantum computers use qubits that can represent multiple states simultaneously [6]. This allows quantum computers to process multiple calculations in parallel, giving them potential advantages for specific complex problems [2].

Second, the computing power scales differently. In classical computers, power increases linearly with the number of transistors. In contrast, quantum computing power grows exponentially with each additional qubit—the number of possible computations is 2^N, where N represents the number of qubits [6].

Finally, operating conditions differ dramatically. Many quantum computers require extremely controlled environments, sometimes at temperatures approaching absolute zero (-273.15°C or -459.67°F) [6]. This is because qubits are extremely fragile—heat, vibration, or electromagnetic interference can cause them to lose their quantum properties [1].

Furthermore, quantum computers excel at solving certain problems that classical computers find intractable, particularly those involving quantum simulation, complex optimization, and pattern recognition in large datasets [6][4].

Understanding Qubits, Superposition, and Entanglement

Image Source: Medium

At the core of quantum computing lies three fundamental principles that give these machines their extraordinary power. To truly grasp how quantum computers operate, we must first understand these key concepts.

Qubits vs Bits: Information Encoding

Classical computers process information using bits—binary units that are either 0 or 1. In contrast, quantum computers use quantum bits or “qubits.” Unlike their classical counterparts, qubits aren’t limited to just two states [8]. They can exist as a complex mathematical combination of both 0 and 1 simultaneously through a property called superposition [9]. This mathematically appears as: |ψ⟩ = α|0⟩ + β|1⟩, where α and β are complex numbers called probability amplitudes [8].

Various physical systems can implement qubits, including trapped ions, photons, atoms, and superconducting circuits [10]. When measured, a qubit will collapse to either 0 or 1 with probabilities determined by |α|² and |β|² respectively [8].

Superposition: Representing Multiple States

Superposition allows qubits to exist in multiple states concurrently [11]. Mathematically, it represents a weighted sum or difference of two or more states [2]. Consider a traditional coin showing heads or tails—in the quantum realm, before observation, the coin exists in a mixture of both states simultaneously [1].

What makes superposition truly powerful is its scaling property. While n classical bits can represent only one of 2^n possible states at a time, n qubits in superposition can represent all 2^n states at once[2]. This exponential scaling enables quantum computers to explore vast solution spaces efficiently.

Entanglement: Correlated Qubit Behavior

Quantum entanglement occurs when qubits become linked in such a way that their quantum states cannot be described independently [12]. Even when separated by large distances, entangled qubits maintain their connection—measuring one immediately affects the other [13].

Consider a system where two entangled particles have a combined spin of zero. If one particle is measured as spin-up, the other must invariably be spin-down [12]. This correlation persists regardless of distance, seemingly defying Einstein’s theory of special relativity [13].

Interference and Measurement in Quantum Systems

Quantum interference allows probability amplitudes of different quantum states to combine constructively or destructively [14]. Much like waves in water, quantum states can reinforce or cancel each other out [15]. Through careful manipulation, quantum algorithms amplify desired outcomes while suppressing unwanted ones [14].

Measurement plays a crucial role in quantum systems. When we measure a qubit, its superposition state “collapses” to either 0 or 1 according to probability rules [16]. Consequently, quantum algorithms must be designed to maximize the probability of measuring the correct solution [7].

How Does a Quantum Computer Work in Practice?

Image Source: Exoswan Insights

Bringing quantum theory into physical reality requires specialized hardware and software components that differ vastly from classical computing systems. Modern quantum computers translate quantum mechanical principles into tangible technological implementations through carefully engineered systems.

Quantum logic gates and circuits

Quantum logic gates serve as the fundamental building blocks of quantum computing, manipulating qubits through unitary operations [17]. Unlike classical logic gates, quantum gates are reversible and can create and maintain superposition and entanglement [18]. Common single-qubit gates include the Pauli-X gate (quantum equivalent of NOT), Pauli-Y, Pauli-Z, and the Hadamard gate, which creates superposition by mapping |0⟩ to (|0⟩+|1⟩)/√2 and |1⟩ to (|0⟩-|1⟩)/√2 [17].

Multi-qubit operations rely on controlled gates like CNOT (controlled-NOT), which flips a target qubit’s state only when a control qubit is |1⟩ [17]. These gates combine to form quantum circuits—collections of qubits with instructions that act sequentially, creating algorithms that process quantum information [19].

Quantum hardware: superconducting vs ion trap

Presently, two leading approaches dominate practical quantum computing implementations:

Superconducting qubits operate at extremely low temperatures () near absolute zero, approximately 10-20 mK[20]. Companies like IBM and Google utilize superconducting circuits with Josephson junctions, where electric current can persist indefinitely through superconducting loops without power [6]. These systems offer faster gate operations but suffer from shorter coherence times [4].

Trapped ion systems use charged atoms (ions) suspended in electromagnetic fields [6]. Each ion stores a qubit in its electronic states, with lasers manipulating these states to perform operations [21]. Although generally slower than superconducting systems, trapped ions provide superior qubit connectivity and longer coherence times, maintaining quantum states more reliably [4].

Notably, researchers at NIST first demonstrated a quantum logic gate using a trapped ion in which they controlled an ion’s internal energy state (first qubit) and its motion (second qubit) [22].

Quantum software: Qiskit and circuit design

In essence, executing algorithms on quantum hardware requires specialized software. , enables users to build circuits, leverage quantum functions, and execute workloads on quantum computers IBM’s Qiskit, the world’s most popular quantum software stack[23].

Quantum programs typically follow this process:

Designers create quantum circuits using frameworks like Qiskit
The software transpiles these circuits into hardware-compatible instructions
The system executes operations as microwave pulses, laser beams, or voltage changes depending on the hardware [20]
Measurement operations convert quantum states back to classical information

Circuit depth—the number of sequential gate layers—roughly corresponds to execution time and affects whether a quantum circuit can run on a given device [19]. As quantum technology advances, improved software tools continue making these powerful but complex systems more accessible to researchers and developers.

Breakthroughs in Quantum Computing in 2025

Image Source: SpinQ

The year 2025 has witnessed remarkable milestones in quantum computing research, with breakthroughs that significantly advance both hardware efficiency and processing capabilities.

GKP Code Implementation in Trapped Ions

Scientists have long sought ways to reduce the physical-to-logical qubit ratio needed for functional quantum computers. The Gottesman-Kitaev-Preskill (GKP) error-correcting code, often called the ‘Rosetta stone’ of quantum computing, has moved from theoretical possibility to physical reality [24]. This approach offers substantial hardware efficiency by encoding a logical qubit into a single quantum harmonic oscillator, though at the cost of increased encoding complexity [25].

Single-atom entangled logic gate by University of Sydney

Researchers at the University of Sydney Nano Institute achieved a groundbreaking milestone by entangling two “quantum vibrations” within a single ytterbium atom [3]. This revolutionary technique taps into the natural oscillations of a trapped ion, allowing precise control of its harmonic motion to manipulate individual GKP qubits [24]. By entangling two quantum states realized as qubits, the team created a logic gate using just a single atom—dramatically reducing the quantum hardware required for operations [26].

IBM’s Qiskit SDK 1.x and CLOPS benchmarking

IBM’s Qiskit has emerged as the highest-performing quantum software development kit available. Recent benchmarking shows Qiskit running 54 times faster than TKET with 30% fewer gate operations [5]. The company also introduced an updated CLOPSh (Circuit Layer Operations Per Second) metric that better reflects how hardware actually executes circuits, allowing for more accurate performance comparisons across different quantum systems [27].

Quantum utility vs quantum advantage

The industry now distinguishes between two key milestones in quantum computing evolution. Quantum utility refers to computation that provides reliable solutions beyond what brute force classical methods can achieve [28]. Meanwhile, quantum advantage represents a significant practical benefit—delivering cheaper, faster, or more accurate solutions than all known classical alternatives [28]. Experts view quantum advantage not as a single breakthrough moment but as an incremental journey of growing capabilities [28].

Real-World Applications and Industry Use Cases

Image Source: Veritis

“There’s magic at the intersection of quantum computing, Artificial Intelligence, and additive manufacturing.” — Hendrith Vanlon Smith Jr., CEO, Mayflower-Plymouth; business and technology thought leader

Practical applications of quantum computing are emerging across multiple industries as the technology matures from theoretical concepts to real-world implementations. Quantum simulation in chemistry and materials

Quantum computers excel at simulating molecular structures and chemical reactions that classical computers struggle to model accurately. This capability enables researchers to predict material properties and design new compounds more efficiently. In fact, quantum simulation allows scientists to study complex systems like superconductors and topological insulators [29]. Recent advances include IBM’s demonstration of a scalable, error-corrected computational chemistry workflow, marking a significant step toward practical quantum advantage in materials science [30].

Post-quantum cryptography and cybersecurity

Given that quantum computers could eventually break current encryption systems, NIST has led a global effort to develop quantum-resistant algorithms. In 2024, NIST released its first three finalized post-quantum cryptography standards [8]. These new algorithms rely on lattice-based problems and hash functions rather than integer factorization, which remains secure against both classical and quantum attacks [8]. Federal agencies now encourage critical infrastructure owners to prepare for the transition to post-quantum cryptography [10].

Optimization in finance and logistics

In logistics, quantum algorithms offer solutions for route optimization, inventory management, and supply chain coordination. ExxonMobil, for instance, is exploring quantum-enhanced maritime inventory routing [9]. Similarly, financial institutions utilize quantum computing for portfolio optimization and risk assessment, with estimated value creation of $2 trillion by 2035 [31].

Machine learning and generative models

Quantum generative models leverage entanglement and superposition to enhance learning capabilities. The recently developed Quantum Denoising Diffusion Probabilistic Model (QuDDPM) demonstrates efficiency in learning correlated quantum noise models and quantum many-body phases [32]. Notably, Quantum Circuit Born Machines (QCBMs) have proven competitive with classical generative models, particularly in low-data regimes [33].

Conclusion

Quantum computing stands at the frontier of technological innovation, poised to transform numerous industries through its unprecedented computational capabilities. Throughout this article, we explored how quantum systems leverage the principles of superposition and entanglement to process information in ways classical computers simply cannot match.

The fundamental difference between classical bits and qubits allows quantum computers to handle exponentially more information states. This capability, coupled with specialized hardware implementations like superconducting circuits and trapped ion systems, creates machines uniquely suited for solving previously intractable problems.

Additionally, the breakthroughs of 2025 have significantly advanced the field. The successful implementation of GKP error-correcting code and the revolutionary single-atom entangled logic gate developed by University of Sydney researchers represent major steps toward practical quantum computing. IBM’s improvements to Qiskit further demonstrate the rapid maturation of quantum software ecosystems.

The real-world applications appear both vast and transformative. From simulating complex molecular structures for drug discovery to developing quantum-resistant cryptography, these systems promise solutions to challenges that have long resisted conventional approaches. Financial institutions, logistics companies, and AI researchers already explore quantum algorithms to gain competitive advantages.

Quantum computing will not replace classical systems but rather complement them, excelling at specific tasks where quantum properties offer natural advantages. The distinction between quantum utility and quantum advantage helps frame realistic expectations as this technology continues to evolve.

The journey from theoretical physics to practical quantum computing has progressed remarkably over recent years. Though challenges remain, particularly in scaling qubits while maintaining coherence, the trajectory points toward increasingly powerful systems with genuine real-world impact. Quantum computing truly represents not just an incremental advancement but a fundamental shift in our computational paradigm, opening doors to possibilities previously confined to the realm of imagination.

Key Takeaways

Quantum computing harnesses quantum mechanics to solve complex problems exponentially faster than classical computers, with breakthrough applications emerging across industries from drug discovery to cybersecurity.

• Quantum computers use qubits that exist in multiple states simultaneously, enabling exponential processing power growth with each additional qubit added.

• 2025 breakthroughs include single-atom logic gates requiring fewer physical qubits and GKP error-correcting codes, dramatically improving hardware efficiency.

• Real-world applications span molecular simulation for drug discovery, post-quantum cryptography for cybersecurity, and optimization for finance and logistics.

• Quantum computing won’t replace classical computers but will complement them for specialized tasks, with the industry projected to reach $1.3 trillion by 2035.

• The technology distinguishes between quantum utility (reliable solutions beyond classical brute force) and quantum advantage (practical benefits over all classical alternatives).

While quantum computers require extreme operating conditions and remain largely experimental, recent advances in hardware efficiency and software development are rapidly moving the field from theoretical concepts to practical implementations that could revolutionize how we approach computational challenges.

FAQs

Q1. What were the major quantum computing breakthroughs in 2025? Key breakthroughs in 2025 included the implementation of GKP error-correcting code in trapped ions, the development of a single-atom entangled logic gate by the University of Sydney, and significant improvements in IBM’s Qiskit software development kit.

Q2. How does quantum computing differ from classical computing? Quantum computing uses qubits that can exist in multiple states simultaneously, unlike classical bits. This allows quantum computers to process exponentially more information and solve certain complex problems much faster than classical computers.

Q3. What are some real-world applications of quantum computing? Quantum computing has applications in drug discovery, materials science, financial modeling, cryptography, and optimization problems in logistics and supply chain management. It’s also being used to enhance machine learning and AI capabilities.

Q4. What is the difference between quantum utility and quantum advantage? Quantum utility refers to quantum computations that provide reliable solutions beyond what brute force classical methods can achieve. Quantum advantage represents a significant practical benefit, delivering cheaper, faster, or more accurate solutions than all known classical alternatives.

Q5. How are companies preparing for the impact of quantum computing on cybersecurity? Companies and government agencies are developing post-quantum cryptography standards to create encryption methods that are resistant to both classical and quantum attacks. NIST has released its first three finalized post-quantum cryptography standards, and federal agencies are encouraging critical infrastructure owners to prepare for the transition.