The Rise of Quantum Computing

Exploring Real World Applications, Challenges, and Momentum

I.                   Introduction

Imagine a global shipping network so vast that even the smallest inefficiencies cost companies millions of dollars every day. Classical computers tackle route planning and inventory management by calculating one possibility after another, a process that, as the numbers grow, quickly becomes unmanageable. In drug discovery, screening billions of molecular formations for promising candidates requires computational power that classical computers simply cannot produce. Real-world bottlenecks, such as complex simulations and massive optimization problems, are exactly the areas where quantum computing promises a breakthrough.

As research and industry investments increase, companies from IBM and Google to ambitious startups are racing to build cloud accessible quantum hardware. Open-source frameworks like Qiskit and Cirq are already letting developers test small-scale algorithms on real quantum machines. However, progress remains slow due to quantum bit (qubit) fragility, error rates, and a steep learning curve for new practitioners.

Quantum computing is transforming industries by solving previously difficult problems, despite facing significant scalability and accessibility challenges. In this essay, I will look at the fundamental ideas behind quantum advantage, assess the current state of technology and its possible uses, and then discuss the obstacles preventing this quantum promise from being realized

II.                   Quantum Principles in Simple Terms

At the heart of quantum computing lies the qubit, the quantum counterpart to the classical bit. A bit (binary digit) is a unit of information. At any given time, a bit must be either 0 or 1. Unlike a bit, however, a qubit can exist in a combination of both states simultaneously – known as superposition. In the book Quantum Computing: The Future of Information Processing, Tiwari, Tyagi, and Nagaraj explain that this “dual state capability allows quantum processors to represent and process a vastly larger set of possibilities with each additional qubit” (Tiwari et al., 2025, p.12)

Superposition can be visualized using a simple coin flip example. In her TED talk, Shohini Ghose invites her viewers to imagine a coin spinning on a table. As long as the coin is spinning, it is neither strictly heads nor tails but holds the possibility of both. Once it lands, however, it is a definite state (Ghose, 2018). This mirrors how measuring a qubit forces it out of superposition and into a specific 0 or 1. When unobserved, a quantum computer can manipulate the value to benefit its goal. Ghose gives a practical example using a private key. The private key is used to encrypt user data. Regardless of the method used, if a hacker were to guess this key and try to decrypt the data, the quantum computer would simply change a value within the key, rendering the previous key invalid (Ghose, 2018).

Entanglement, the second key principle, is a non-classical connection between qubits. When two qubits are entangled, the state of one instantly changes the state of the other, regardless of the distance separating them. According to Shohini Ghose (2018), in her TED talk, her “favorite quantum application is teleportation of information from one location to another without physically transmitting the information. Sounds like sci-fi, but it is possible, because these fluid identities of the quantum particles can get entangled across space and time in such a way that when you change something about one particle, it can impact the other, and that creates a channel for teleportation. It’s already been demonstrated in research labs and could be part of a future quantum internet” (07:46).

There is also a third fundamental principle besides superposition and entanglement: quantum interference. In superposition, qubits can be controlled to create constructive interference, amplifying correct answers, or destructive interference, suppressing incorrect ones, allowing quantum algorithms to efficiently search a large number of solutions, prioritizing the most probable outcomes. Together, superposition, entanglement, and interference form the backbone of quantum advantage — the ability of quantum systems to solve problems currently difficult for classical machines, opening doors to breakthroughs in fields from drug discovery and materials science to financial modeling and artificial intelligence.

III.                   Technological Momentum

IBM, Google, Amazon Web Services (AWS), and Microsoft are among the most powerful tech companies in the race to build quantum computers. These businesses are making huge investments in cloud infrastructure, algorithm development, and hardware research to realize the promise of quantum computing. IBM, for example, has rolled out a publicly available roadmap that shows its plans for scaling up qubit counts while improving fidelity. Meanwhile, Google achieved “quantum supremacy” in 2019 by showcasing a quantum processor that could perform a task in seconds that would take a classical supercomputer thousands of years. This achievement set a new benchmark for quantum computing momentum.

Cloud accessibility is also improving. AWS offers Amazon Braket, a platform that enables developers to experiment with quantum algorithms using simulators or real hardware, without requiring actual quantum machines.

On the technical side, breakthroughs like algorithmic cooling - the process of reducing thermal noise in qubits- have improved coherence times, making quantum operations more stable. Hybrid systems that pair quantum processors with classical control units are also improving, allowing for practical algorithms in optimization and machine learning that take advantage of both computing paradigms.

Open-source frameworks also play a key role in the development cycle. Since IBM’s Qiskit and Google’s Cirq allow users to simulate quantum circuits, design algorithms, and run experiments on real devices, they have become the training ground for the next generation of quantum and software engineers.

These efforts show a clear trend – quantum computing is not confined to academic labs any longer. It is evolving into an increasingly available field. As research continues, large-scale quantum computers will become a reality, “paving the way for a future where quantum technology is seamlessly integrated across industries” (Tiwari et al., 2025, p.91)

IV.                   Practical Applications in Different Industries

Quantum computing is beginning to reshape how industries tackle their most complex problems, revolutionizing areas where problem-solving has hit a computational limit. Its early-stage applications are showcasing just how drastically new computation models can change the norms.

Quantum systems are highly effective in biophysical research and medication discovery in medicine. It is challenging for classical computers to duplicate molecular interactions at the atomic level accurately, but quantum computers can. According to Tiwari et al. (2025), drug discovery times can be shortened by using simulation platforms that can compute billions of chemical combinations simultaneously (p. 84) .

Simulation, a very complex task for current computers, also benefits from quantum innovation. Quantum processors keep the resource requirements manageable as the system grows. Rather than simulating the entire dimensional space, this approach encodes only the key information—mean values and variances—into qubit states. As Barthe et al. (2025) explain, “the input qubit state [is] preparable in polynomial time and the quantum circuit require[s] only polynomially many gates” (p. 4). Because both the number of qubits and the gate count scale only polynomially with the number of modes, the method can be implemented effectively on today’s quantum hardware.

In finance, quantum algorithms offer new efficient ways to solve optimization problems that involve risk and return. Ghosh (2025, para. 12) reports that institutions are now exploring hybrid quantum-classical portfolio-selection routines that use quantum superposition and entanglement to evaluate risk-return trade-offs across thousands of assets in parallel. Early prototypes show that these quantum-enhanced solvers could meet tight, real-time deadlines and, as devices scale and error correction improves, may begin to outperform classical optimizers on complex portfolio-construction tasks.

Fraud detection is another area where quantum systems shine. Nguyen et al. (2024) found that quantum systems are more sensitive to odd transaction behaviors than classical systems. This implies the potential to improve financial security significantly.

Because quantum computing offers advanced techniques for improving complex processes, it shows a great opportunity in the manufacturing and logistics fields. Its unique ability to manage and evaluate massive amounts of data at once makes it possible to distribute resources and make decisions more effectively, which eventually boosts output and simplifies operations in these industries. Some problems scale poorly on classical systems, such as distributing manufacturing resources efficiently, balancing energy use between factory systems, and scheduling jobs across suppliers. For these optimization issues, quantum algorithms—especially those that use Gaussian bosonic circuits—are ideal. “In keeping with computational complexity theory, our goal is to show that the task of simulating large Gaussian bosonic circuits can be mapped to other problems that are known to be hard for classical computers, but easy for quantum ones,” García-Martín explains (Science X staff, 2023, para. 8). This highlights why logistics is a natural fit for quantum computing. Garcia-Martin and his colleagues show that quantum computing can unlock solutions that were previously out of reach for our current systems.

Quantum sensors are also being applied to predictive maintenance. As stated by IEEE Quantum Technical Community (n.d.), quantum-enhanced analytics can detect subtle patterns in equipment data to identify potential failures earlier and more accurately than classical approaches. These systems could drastically reduce downtime and improve efficiency and costs.

V.                   Challenges and Ethical Concerns

Quantum computing promises to revolutionize many fields by making use of quantum bits’ superposition and entanglement. It is important, however, to understand the bottlenecks and ethical implications that come with this technology.

Quantum decoherence is currently the biggest obstacle to quantum computing. Quantum bits (qubits) lose their ability to exist in a superposition state as a result of interactions with their surroundings. This loss of quantum information blocks advancement because quantum algorithms rely on qubits retaining a constant superposition during computations. Qubits behave like classical bits when superposition and entanglement, which are essential for quantum parallelism, are absent. Therefore, decoherence limits the number of operations that can be performed before noise builds up and makes the computation unreliable. For quantum computers to reach their full potential and address issues that traditional supercomputers are unable to, they must overcome decoherence.

Beyond decoherence, scalability is also a major issue. “While quantum computers have shown impressive performance for some tasks, they are still relatively small compared to classical computers. Scaling up quantum computers to hundreds or thousands of qubits while maintaining high levels of coherence and low error rates remains a major challenge.” (Matt Swayne, 2024, para. 4). This shows that simply adding more qubits is not the solution. Each additional qubit adds new complexities in terms of control wiring and thermal management. Current quantum processors hold 10 to a few hundred qubits, but practical quantum applications are estimated to need thousands to millions of qubits to properly function.

Development of suitable quantum algorithms is an ongoing challenge. While we do have algorithms – such as Grover’s algorithm for efficient database searching – that demonstrate quantum computing’s potential, the discovery of new practical algorithms are still in early stages. Bridging the gap between theoretical advantage and real-world applications will be a significant challenge, but it is not impossible as researchers continue to make progress to close this gap.

The immense computational power of quantum computing also raises ethical concerns. The most obvious one is the threat to current cryptographic systems. Theoretically, algorithms like Shor's algorithm could crack popular public-key encryption techniques like elliptic curve encryption and RSA, which are used in national security systems, secure communications, and financial transactions. This means a global transition to post-quantum cryptography (PQC) is necessary, which involves creating new cryptographic algorithms that are resistant to quantum attacks.

National security is also another area that could be impacted. Advanced quantum systems could tip the balance of power by giving countries a huge advantage in military applications and information gathering. International cooperation and rules between nations would be required in order to stop this.

Lastly, applications such as artificial intelligence and machine learning might misuse quantum computing. A quantum-enhanced AI model would have far better capabilities than current models, raising concerns about accountability and unintended consequences.

VI.                   Why Do We Need It?

Quantum computing is no longer just an academic experiment. Continuing its research despite the challenges could result in great benefits for society. Quantum simulations could significantly accelerate the development of new medications, resulting in cures for currently untreatable diseases. In material science, the ability to create materials with new properties, from superconductors to more efficient batteries, could revolutionize transportation and energy efficiency.

Although challenging, researchers are making very fast progress. The threat to cryptographic standards is no longer just hypothetical, but a present concern. Although fully fault-tolerant quantum computers are still years away, industries that are not prepared for this cryptographic transition risk large breaches of data and national intelligence. The breakthroughs promised by quantum computing could create a large market of highly skilled jobs, so understanding its development is important for mitigating risks and understanding how to use the technology responsibly.

VII.                   Conclusion

Quantum computing is set to bring in a new era with the potential to revolutionize industries and provide answers to some of the most difficult problems facing society. From revolutionizing materials science and drug discovery to enhancing financial modeling and logistics, the ideas of superposition, entanglement, and interference offer a substantial advantage over classical systems. However, achieving this promise will require overcoming major technological barriers, especially those related to scalability, quantum decoherence, and the creation of reliable error correction. The potential of quantum computing also demands proactive and careful consideration of its profound ethical and societal implications, especially regarding privacy, economic disruption, national security, cryptographic security, and the possibility of abuse.

The progress in this field is apparent in the continued investment from top tech companies, alongside rapid developments in algorithms and cloud accessibility. Last but not least, the exploration of quantum computing is an important effort that needs constant study, global cooperation, and thorough ethical understanding to ensure that its potent potential is applied sensibly for the good of society.