Classic, a Tel Aviv-based startup that provides A model for building quantum algorithms, announced working with Rolls-Royce to implement new computational algorithms for fluid dynamics. Rolls-Royce will be able to create, enhance and evaluate scalability Quantum Algorithms With a classic platform. Rolls-Royce will be able to apply computational fluid dynamics techniques in a hardware-independent manner.

Complex numerical simulations of heavy lift for liquids and gas are the focus of computational fluid dynamics (CFD). CFD is essential for improving new equipment designs as it can be used to improve aerodynamics and thermodynamics, among other things. By combining quantum computing and traditional methods, collaboration will take advantage of the advantages of each technology.

classic The synthesis engine implicitly explores a wide design space for potential circuits to meet each user’s needs and provide state-of-the-art optimizations – leaving users with more resources, be it time, qubits, quantum gates, or precision. Such exploration at the functional level is only possible when synthesizing circuits from functional models, an approach that is fundamentally different from current quantum solution schemes.

Capacity building is an important step that must be taken in order to prepare for this new computing age, which is expected to lead to faster computations for quantum computers compared to conventional computers in the future. Rolls-Royce implements optimized, hardware-independent algorithms for current and future quantum computers with the help of Classiq.

**Quantum Era**

In order to prepare for “edge,” when quantum machines can solve the same equations faster than the fastest supercomputers, Rolls-Royce engineers will work on ways to solve and predict fluid dynamics. It will cover CFD Algorithms, which deals with heavy and complex numerical simulations of liquids and gases.

The quantum Harrow-Hassidim-Lloyd (HHL) algorithm, which can solve linear system problems with exponential acceleration in the classical way, is the basis for many important quantum computing algorithms.

The HHL method is designed to quickly solve many linear equations. Its main assets are the availability of a hybrid environment, where programmers can write Python code and direct both traditional and quantum machines.

By using the HHL equations and applying them to fluid dynamics, it will be possible to solve the nonlinear parts of the equations on a conventional supercomputer and then send the linear parts to a QPU (quantum processing unit), which can complete the process more quickly.

While most discussions of quantum computing focus on the time when quantum computers will be able to consistently outperform their classical counterparts, the reality of quantum computing will be a hybrid approach for many application cases.

Rolls-Royce will use the Classiq platform to design quantum algorithms for CFD simulation. CFD is essential for many space use cases that include airflow simulation. CFD is a very complex set of partial differential equations, which cannot be solved by classical computers and even HPCs (it takes exponential time with the size of the problem). Quantum computers are likely to provide an exponential acceleration of these computations. Python itself is good because many programmers are used to it. Having said that, Python should be an encapsulation of a language specific to a specific field of quantum computing. That’s exactly what we’ve done with QDL – Quantitative Description Language,” commented Nir Minerby, CEO of Classiq.

Classic addresses challenges in the development of quantum computing by bridging the gap of complex quantum logic. The company is building a new layer of quantum software package, which increases the level of abstraction and allows developers to implement their ideas and concepts without having to design a specific quantum circuit at the gate level.

**Computational Fluid Dynamics (CFD)**

At a significantly expanding pace, modern industry creates and manufactures more complex items. Production companies need tools that enable them to research and predict potential problems in order to reduce potential errors during the design process and time to market. This is necessary for them to remain competitive.

When prototyping and producing a product as well as throughout the design and development stages, simulation allows for the knowledge required to enhance the product to be gained.

Through the use of numerical methods, computational fluid dynamics allows simulation of both the behavior of liquids and gaseous fluids. It is used in a variety of industries, including automotive, aerospace, and electronic cooling systems.

The numerical method that enables the computational study of fluid mechanics is known as computational fluid dynamics. The Navier-Stokes equations, which define fluid mechanics mathematically through its basic variables such as pressure, temperature, density, velocity, and viscosity, can be solved using computational fluid dynamics (CFD).

**Navier-Stokes equations**

The Navier-Stokes equations are the equations that describe the motion of a real fluid. They consider the contribution of all the forces acting on an infinitesimal element of scale and its surface. Given a given mass of fluids in a region of space, two types of forces act on it: volume forces and surface forces.

Scale forces are expansive forces that result from external causes of the area considered. These reasons are gravity. Actions due to electric and/or magnetic fields; Non inertial forces.

Since these forces are proportional to volume, they are expressed per unit volume. Surface forces are forces of an intense nature and can be traced back to the interaction of the fluid under study with the rest of the studied physical system expressed through boundary surfaces.

The Navier-Stokes equations are a system of three equilibrium equations (partial derivative equations) of continuum mechanics, which describe a linear viscous fluid; In them Stokes’ law (in kinetic equilibrium) and Fourier’s law (in energy balance) are presented as foundational laws of matter. The equations are named after Claude-Louis Navier and George Stokes.

**CFD simulation**

Any equipment, machine or structure whose operation involves fluid interaction, whether of internal or external flows, may benefit from CFD fluid dynamics simulation. Calculate wind loads on civil and military communications antennas, roofs, tensile structures, and radomes, while accurately simulating a wind tunnel test.

- To increase the efficiency and uniformity of the flow and heat, improve the geometry of the internal channels of the machine.
- Calculate heat transfer in liquids and solids, such as cooling electrical or electronic equipment.

CFD studies make it possible to simulate situations such as tsunamis, meteorological events, and environmental ramifications in addition to traditional industrial uses. Weather centers use supercomputers because this type of study can require a great deal of computational power.

**CFD for you**

It is necessary to reach a certain degree of abstraction that makes it easy to write algorithms for quantum computers and enables the algorithms to be implemented on different hardware platforms. A system will be developed to manage and automate the process as much as possible so that the upper tier is hardware-independent and operates in a hybrid environment, according to Classiq. The company will provide and create improved hardware-less quantum circuits, allowing them to be used in various quantum computing platforms to be developed in the future.

All this will also enable Rolls-Royce to achieve zero CO2 emissions due to ongoing, secondary but critical technological developments at all levels.

Quantum machines will be trustworthy enough to perform comprehensive analyzes within a few years. The goal of the algorithms is to increase the ability of devices to adapt to all the industrial applications that require them.

A modern CPU is useless without an operating system and software support tools in today’s computer world. The same is true for a quantum computer. As important as the hardware is, the software is also important for the quantum revolution.

The complexity of writing quantum programs has another unfortunate side effect: it is difficult to find experts in quantum programming, because this is different from classical programming. Quantum programming experts need to know both software engineering and quantum physics.

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