[SPONSORED GUEST ARTICLE] The relentless progress of technology has seen supercomputers achieve remarkable feats, but the miniaturization of processors is now at the limits of classical physics. While AI has revolutionized problem-solving, it hasn’t lessened the need for computational power. Quantum computing, rooted in quantum mechanics, promises to expedite solutions to complex problems, aiming for faster and more precise calculations for certain tasks. Although intricate, the potential of quantum computing to address intricate challenges is exciting, and we provide an educational introduction to this topic.
Quantum Computing: How to Build a Quantum Processor
Quantum computing, rooted in early 20th-century quantum mechanics, relies on “superposition” and “entanglement.” A qubit, akin to a classical bit, embodies quantum information and exhibits these properties under certain conditions. Qubits are created using atoms, ions, photons, silicium structures, or superconducting materials, but perfect qubits are not yet achievable. Scaling to thousands or millions of qubits presents significant scientific and industrial challenges that will take years to overcome.
The Current Generation of Quantum Computers and the Era of Perfect Computers
The current generation of quantum computers, known as the NISQ era, is characterized by a small number of imperfect qubits and inherent errors or “noise.” Despite global efforts to develop these systems, they are limited to a few hundred qubits, which is insufficient compared to the thousands or millions required. The future FTQC era aims for “Fault-Tolerant Quantum Computers” or LSQ (“Large Scale Quantum”), which will be capable of extremely complex processing beyond the reach of today’s most powerful classical computers. However, this ideal is not expected to be achieved for another 10 to 15 years.
Quantum Computer Families
Beyond the different qubit technologies mentioned below, two main programming models – digital and analog – will fundamentally impact how an application is developed.
A digital quantum computer with gates, also known as a universal quantum computer, theoretically supports any quantum algorithm. In practice, quantum circuits are created by applying gates to qubits, such as q0, q1, q2, etc., in a sequence that includes quantum gates, measurements, qubit initializations, and other operations, akin to classical logic circuits.
Examples of adder circuits: on the left, a classical logic circuit; on the right, a quantum circuit.
The analog is divided into two subcategories: quantum annealing and the simulator. Quantum Annealing (QA), a branch of quantum computing, seeks the lowest energy state in the Ising model to solve minimization problems, useful for combinatorial optimization. Quantum simulators, meanwhile, simulate quantum phenomena to analyze complex systems like molecules or ‘N-body’ problems.
Quantum at Eviden and the Qaptiva™ Strategy
Eviden’s approach to quantum computing involves developing a quantum emulator, Qaptiva™ solution, to focus on algorithm and application development for quantum processors. This allows industry and research professionals to prepare for when the hardware matures. This solution supports the development and execution of quantum algorithms on both the emulator and real quantum computers. This solution allows for the development, fine-tuning, and execution of quantum algorithms on the Qaptiva™ emulator, NISQ machines (real quantum computers), and later on FTQC/LSQ machines.
The Qaptiva™ solution enables emulation of various qubit technologies for detailed characterization and adaptation of generic quantum code to specific processors. Similar to writing C++ code without concern for the operating system, Qaptiva™ allows coding of gate-based quantum circuits without worrying about the processor type. This flexibility helps developers create hardware-agnostic quantum solutions. Eviden also focuses on forming strategic partnerships in the quantum field.
Also, to help familiarize myself with quantum computing, Eviden developed myQLM, a lightweight version of the Qaptiva™ software tools that use the Python language interface. myQLM is a free quantum programming software that can simulate quantum computations on personal computers and is interoperable with other quantum programming tools. For example, it can translate quantum circuits between Qaptiva™ and IBM’s Qiskit.
Therefore, myQLM is the perfect environment to begin developing quantum computing applications. To familiarize yourself with the subject, you can access comprehensive documentation and Jupyter notebooks at https://myqlm.github.io/.
Quantum Computing, for What Uses?
The challenge of quantum computing is not to replace classical computing but to address highly complicated problems that are inaccessible even to the most powerful HPC computers on the planet. Quantum computing aims to solve complex problems beyond the scope of classical HPC computers, potentially revolutionizing fields like drug design and material science for energy transition. Unlike classical programming, quantum programming requires a complete rethinking of algorithms, leading to fewer quantum algorithms:
As a result, many industries are interested in it. Here are a few areas directly concerned:
- Molecular modeling: examining the exact structure of a molecule to determine its properties and understand its potential interactions with other molecules.
- Finance: by performing massive and complex calculations, the quantum computer could thus make financial forecasts and allow for a better understanding of certain economic phenomena.
- Logistics: modeling to help optimize logistics and planning of workflows associated with supply chain management.
- Health: accelerate the understanding of diseases and improve the accuracy of treatments.
For more information about Eviden’s Quantum Computing Portfolio, visit us at Eviden Quantum Computing.
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Olivier Hess, Eviden
Author: Eviden’s Olivier Hess is the Head of Quantum Computing in France and serves as the Global Quantum Computing Technology Advisor. With extensive experience in HPC and Quantum Computing at IBM, Olivier joined Eviden in 2021. His role involves spearheading the development of quantum computing consulting services, advancing Eviden’s solutions, and overseeing collaborations and partnerships within France. He earned his PhD in Quantum Chemistry from the University of Paris VI, France, in 1989.
