Quantum Computing definition
Quantum computing is a type of computing that uses quantum-mechanical effects, such as superposition and entanglement, to process information in quantum bits, or qubits. For certain problems, including simulating molecules and breaking widely used encryption, quantum computers could eventually outperform classical computers, though today's machines remain small, noisy and error-prone.
How does quantum computing work?
A classical bit is either 0 or 1. A qubit can be in a superposition, a combination of 0 and 1 described by probabilities, until it is measured and settles on one value. Qubits can also be entangled, so their measured values are correlated in ways no classical system can reproduce. Quantum algorithms apply sequences of gates that use interference to strengthen paths leading to correct answers and cancel out paths leading to wrong ones.
Building qubits is extraordinarily hard. Leading approaches include superconducting circuits cooled close to absolute zero, used by IBM and Google, trapped ions used by Quantinuum and IonQ, neutral atoms and photonics. Qubits lose their quantum state quickly through noise, a problem called decoherence. Quantum error correction combines many physical qubits into one reliable logical qubit, and achieving it at scale is the field's central engineering challenge.
Potential applications
- Chemistry and materials: simulating molecules for batteries, catalysts and fertilizers.
- Drug discovery: modeling interactions that are intractable for classical computers.
- Cryptography: Shor's algorithm could break RSA and elliptic curve encryption on a large, error-corrected machine.
- Optimization: logistics, portfolios and scheduling, where advantage is still unproven.
- Search and sampling problems with proven but more modest speedups.
- Machine learning: an active research area with speculative benefits.
- Financial risk modeling and Monte Carlo simulation, also still being researched.
Quantum computing and cybersecurity
The most urgent business impact is on encryption. Attackers can already collect encrypted data today and store it until a capable quantum computer can decrypt it, a strategy known as harvest now, decrypt later. Data that must stay confidential for many years is therefore at risk even before such machines exist.
In 2024, the US National Institute of Standards and Technology published its first post-quantum cryptography standards, covering new algorithms for key establishment and digital signatures designed to resist quantum attacks. Major browsers, operating systems and cloud providers now use them in production, often in hybrid modes combined with classical algorithms.
The current state of quantum computing
Today's devices are often described as noisy intermediate-scale quantum (NISQ) machines: tens to a few thousand physical qubits without full error correction. Google reported in 2019 that its processor had performed a specific sampling task faster than classical supercomputers could, though the task had no practical use. In late 2024 its Willow chip showed errors falling as more physical qubits were combined into logical qubits, an important error-correction milestone, and in 2025 Google reported a verifiable quantum advantage on Willow with its Quantum Echoes algorithm. Companies can experiment through cloud services such as IBM Quantum, Amazon Braket and Azure Quantum using frameworks like Qiskit and Cirq.
What businesses should do now
For most organizations, the priority is security rather than quantum algorithms. Build an inventory of where cryptography is used, identify data that must stay secret for a long time, and plan migration to post-quantum algorithms, preferring crypto-agile designs that can swap algorithms without rewriting systems. Companies in chemistry, materials, pharmaceuticals and finance may also run small research projects through cloud quantum services. Nexzem helps clients assess cryptographic exposure and plan post-quantum readiness as part of security modernization.