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Among quantum computing’s key milestones have always been demonstrating possibilities to “execute entire algorithms’ with a scaling speedup relative to ordinary, so-called classical computers. Presently, e.g. quantum technologies are already transforming financial sector by offering exponential speedups and secure encryption. These innovations also provide strategic insights for states’ governance, signaling a shift toward a more resilient and data-driven political economies and financial systems.
Introduction
The article provides some insights on emerging applications of quantum technologies; however, still much work remains to be done before quantum computers can be claimed to have solved a practical real-world problem.
In breaking down the quantum technology user-cases, as well as showing present situation and perspectives, particularly, the advancements that can and could reshape industries and enhance global development and security through quantum computing.
Unprecedented exponential speedup in quantum computing has been demonstrated by using IBM’s 127-qubit processors, the process that showcasing that quantum machines can significantly outpace classical computers.
This speedup is unconditional in the sense that quantum technologies do not rely on any unproven assumptions, marking a key milestone in the field. Techniques such as optimized data input, compressed quantum operations, dynamical decoupling, and measurement error mitigation played crucial roles in achieving this breakthrough. Hence, “unconditional”, means that quantum algorithm doesn’t rely on any unproven assumptions compared to classical digital algorithm.
Source: https://www.sciencedaily.com/releases/2025/06/250629033459.htm. Reference to: Phattharaporn Singkanipa, Victor Kasatkin, Zeyuan Zhou, Gregory Quiroz, Daniel A. Lidar. Demonstration of Algorithmic Quantum Speedup for an Abelian Hidden Subgroup Problem. – Physical Review X, 2025; 15 (2) DOI: 10.1103/PhysRevX.15.021082.
General reference to: https://intelligence.weforum.org/topics/a1GTG0000000VqD2AU/publications/52aa46bf611b4722888dbb6bb370ecb6?emailType=Strategic%20Intelligence%20Weekly&ske=MDAxNjgwMDAwMDdQUEl3QUFP
The changing computation’s methods
In 1994, the mathematician Peter Shor devised an algorithm that would let quantum computers “factor big numbers exponentially faster than classical machines”; that speedup matters because a so-called “fast-factoring algorithm” could render most data-encryption methods useless.
For more than 30 years, researchers have been trying to boost and guard against the power of future quantum computers.
But the Shor’s factoring algorithm has had some limitations: i.e. the bigger the number “to factor”, the bigger and better is the used quantum computer entity; thus, cracking an encryption scheme would require a quantum computer running Shor’s algorithm on hundreds of thousands of efficient quantum bits, or qubits.
The “puzzle” is still not resolved by today’s digital devises. Some researchers described, how to factor any number with considerably fewer qubits, just one showing how to factor an integer of any size with a single qubit and three components known as oscillators, i.e. readily available devices typically associated with other quantum technology, like optics systems.
The new approach uses another way to encode information: classical computers use bits, which can take one of two values; qubits, the quantum equivalent, can take on multiple values, because of the vagaries of quantum mechanics. But even qubits, once measured, can take on only one of two values, a 0 or a 1. Others are focusing on ways to encode information with continuous variables, meaning they can take on any values in a given range, instead of just certain ones.
The secret to Shor’s algorithm, argue researchers, is that it uses the number that it is “factoring to generate a periodic function, which has repeating values at regular intervals”.
Then it uses a mathematical tool called a quantum Fourier to transform and identify the value of that period, i.e. how long it takes for the function to repeat. From there, some straightforward algebra can reveal the original number’s factors.
Thus, modern researchers proved that in a “system using quantum oscillators instead of qubits, the dynamics of those physical components could indeed perform the mathematical work of factoring (without having to simulate the discrete values of qubits). The single qubit in their system reads and organizes information in the oscillators but doesn’t perform the actual computation, as qubits do in other quantum computers. Like Shor’s algorithm, the new approach factors integers in a reasonable amount of time.
However, the larger the number to be factored, the more energy the oscillators require to do the math: consequently, the process of “factoring a large number uses only one qubit, but it requires a near-unthinkable amount of energy”.
Still other researchers postulate that “qubits don’t have to be the only engine of computation, with oscillators playing the role of basic information carriers: hence, it is possible that other components already present in quantum devices could also be leveraged to perform computations and reduce energy consumption.
Source and citations from “Quantum Magazine” at: https://www.quantamagazine.org/new-quantum-algorithm-factors-numbers-with-one-qubit-20250609/?print=1
Case study: practical example
One of numerous opportunities quantum technologies can represent is that of banking sector, according to a new report from the World Economic Forum, where quantum technologies’ leaders (in collaboration with Accenture), draws on insights to show the ways these technologies are being tested and most likely to be deployed in the long term. Besides, banks are piloting quantum tools for risk analysis and fraud detection.
Key applications of quantum technologies in the banking sector fall into three areas:
– Quantum computing, providing for more accurate risk modelling, fraud detection and portfolio optimization.
– Quantum security and communications that secure theoretically unbreakable encryption through methods such as quantum key distribution (QKD) and quantum random number generation (QRNG).
– Quantum sensing making precise measurement capabilities that may be used to heighten the synchronization of high-frequency trading (HFT) algorithms.
Citations from: https://www.weforum.org/stories/2025/07/banking-quantum-era-fraud-detection-risk-forecasting-financial-services/