QUA has been launched by Quantum Machines as a standard universal language for quantum computing. QUA allows researchers to intuitively program even complex quantum programs that are tightly integrated with classical processing and real-time decision-making, which provides hardware and software for the control and operation of quantum computers.

The language is the first to address all requirements of an anticipated quantum computing software abstraction layer. A primary challenge with quantum research and development is that every quantum computer has its own unique hardware, coded in the researchers’ language of choice. The unique nature of every system results in teams spending inordinate amounts of time coding and programming new programs and algorithms, with any variation requiring either restarting the process or even re-routing the control hardware itself.This becomes an extremely time-consuming process and it is difficult to scale to more complex systems and algorithms.

QUA allows researchers to intuitively program even complex quantum programs that are tightly integrated with classical processing and real-time decision-making, which provides hardware and software for the control and operation of…
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QUA is a pulse-level programming language for quantum devices, and it is the first language designed specifically as a universal quantum computing software abstraction layer. QUA unifies universal quantum operations in their “raw” or pulse-level format with universal classical operations.

QUA Use Case

The language allows users to code even programs that are far beyond expression today, from complex AI-based multi-qubit calibrations to multi-qubit quantum-error-correction.This helps teams save resources both in terms of redesigning software and hardware architectures, and in readopting their already programmed algorithms in the future. To achieve this, several different criteria had to be fulfilled to fit the distinct structure of quantum algorithms and quantum programming: semantical, technological, and commercial.

QUA is being billed as the first language to combine universal quantum operations at the pulse level, together with universal classical operations, namely, Turing-complete classical processing, and comprehensive control-flow.

From a technological and commercial perspective, QUA was developed to be very intuitive while relying on QM’s proprietary compiler, XQP, to do the heavy lifting for optimizing the many intertwined quantum and classical operations. XQP compiles quantum programs to QM’s Pulse Processor assembly language, which can then run them with extremely low latencies and precision, according to the company.

QUA is integrated into Quantum Machines’ existing Quantum Orchestration Platform. Teams can run even the most complex quantum-error-correction and hybrid quantum-classical algorithms right out of the box.QUA is the first-ever programming language designed with the needs of quantum research in mind and offers teams a powerful and intuitive language designed not only for their present needs but also those of the future.”

About Quantum Machines

Quantum Machines is a start-up developing control and operation systems for quantum computers. Quantum Machines was founded in 2018 and is headquartered in Tel Aviv, Israel. The company also develops innovative software, hardware, and electronics, combining a range of classical engineering in the field of electrical, hardware, and software engineering, with the science and technology of quantum computing. It utilizes a range of skills such as algorithmics, digital signal processing, RF microwave engineering, machine learning, and quantum physics to push their limits.

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Researchers at ETH Zurich have designed the first programming language, Silq, that can be used to program quantum computers as simply, reliably and safely as classical computers. Silq is the very first high-level programming language for quantum computers. High-level programming languages are more expressive, meaning that they can describe even complex tasks and algorithms with less code.

Silq programming language

Silq is a new high level quantum programming language developed by ETH Zurich. The intent is do provide a language that enables code that is shorter and simpler, less error prone, and more intuitive that existing lower level programming languages. The developers indicate that this will provide programs with much fewer lines of code than other programming languages; on average -46% versus Q# and -38% versus Quipper. A key feature is that it provides for automatic uncomputation of temporary values. This is more complicated than resetting a temporary classical value because the temporary qubits are entangled with other qubits and resetting it by measuring it can have some unintended consequences.  For now, Silq does not generate code for any existing hardware backend and only supports its own simulator.

Silq is the first quantum programming language that is not designed primarily around the construction and functionality of the hardware, but on the mindset of the programmers when they want to solve a problem—without requiring them to understand every detail of the computer architecture and implementation.

Silq is also the first programming language that automatically identifies and erases values that are no longer needed. It’s a major breakthrough in terms of optimizing the programming of quantum computers.

As a key novelty, Silq helps to bridge the conceptual gap between classical and quantum languages. As a consequence, Silq (i) lowers the entrance barrier for non-expert quantum programmers, (ii) generally helps to express complicated algorithms cleanly and concisely, and (iii) facilitates a tech-transfer of 50+ years of programming and analysis techniques developed for classical computing, to the domain of quantum programming.

Comparison

While traditionally quantum algorithms were often specified in terms of circuits, quantum languages express quantum algorithms more conveniently as source code. However, existing quantum languages force the programmer to work at a low level of abstraction, still essentially specifying quantum circuits that explicitly apply quantum operations to individual quantum bits. As a consequence, implementing quantum algorithms in these languages is tedious and error-prone.

In contrast, Silq supports a descriptive view on quantum algorithms that expresses the high-level intent of the programmer. Then, the compilation of these algorithms to low-level quantum circuits becomes a second-order concern that can be handled by a specialized compiler, much like in classical programming languages.

Experimental evaluation demonstrates that Silq programs are significantly shorter than equivalent programs in other quantum languages (on average -46% for ​Q#,​ -38% for ​Quipper​), while using only half the number of quantum primitives. Thus, Silq programs are not only shorter, but also easier to read and write, as they require less primitives and concepts.

Most of over evaluation focused on Q#, because (i) it is one of the most widely used quantum languages, (ii) we consider it to be more high-level than ​Cirq or ​QisKit​, and (iii) the Q# coding contests from ​2018 and ​2019 provide a large collection if Q# implementations we were able to leverage for our comparison.

Team​

Silq was developed by ​Benjamin Bichsel​, ​Maximilian Baader​, ​Timon Gehr​, and Prof. Martin Vechev​, who are all part of the SRI Lab, a research group at ETH Zurich’s Department of Computer Science.

Resources

• Silq’s webpage (​http://silq.ethz.ch/​) offers a detailed introduction of Silq’s ​key concepts ​, a demonstration of ​Silq’s benefits over Q# ​, concrete ​examples of Silq algorithms, instructions​ on installation, and much more.
• Silq’s parser, type checker, and simulator are publicly available at GitHub and licensed under the Boost Software License 1.0.

Key Benefit – Automatic Uncomputation

The key benefit of Silq is that it automatically (without intervention from the programmer) handles ​uncomputation of temporary values. In the following, we explain the necessity of uncomputation, and the benefits of automating it.

Analogously to the classical setting, quantum computations often produce temporary values. However, as a key challenge specific to quantum computation, removing such values from consideration induces an ​implicit measurement ​collapsing the state. In turn, collapsing can result in unintended side-effects on the state due to the phenomenon of ​entanglement​. Surprisingly, due to the quantum principle of ​deferred measurement​, preserving values until computation ends is equivalent to measuring them immediately after their last use, and hence cannot prevent this problem.

To remove temporary values from consideration without inducing an implicit measurement, algorithms in existing languages must explicitly uncompute all temporary values, i.e., modify their state to enable ignoring them without side-effects. In particular, even dropping the result of a sub-expression like ​x||y in ​(x||y)||z requires explicitly applying gates that uncompute this value, essentially forcing the programmer to perform manual memory management.

This results in a significant gap from quantum to classical languages, where discarding temporary values typically requires no action (except for heap values not garbage-collected). This gap is a major roadblock preventing the adoption of quantum languages as the implicit side-effects resulting from uncomputation mistakes, such as silently dropping temporary values, are highly unintuitive.

In contrast, Silq is comparable to high-level languages like Rust, in that it automatically handles uncomputation in a safe way. Among other benefits, this allows us to naturally support nested expressions, as known from classical languages.

Key Technique – Quantum Type System.​

Silq introduces a novel ​quantum type system which exploits a fundamental pattern in quantum algorithms, stating that uncomputation can be done safely if (i) the original evaluation of the uncomputed value can be described classically, and (ii) the variables used to evaluate it are preserved and can thus be leveraged for uncomputation.

Silq’s quantum type system allows it to detect this pattern, ensuring uncomputation is possible. Moreover, Silq also detects when uncomputation is not possible. In this case, Silq reports an error—before even running the algorithm. As a consequence, all Silq algorithms are physical: they can be realized on a quantum computer, and never attempt physically impossible operations like invalid uncompuation or reversing a measurement.

Future Benefits.

Silq is expected to advance various tools central to programming quantum computers. First, Silq compilers may require fewer quantum bits, e.g., by more flexibly picking the time of uncomputation. Second, static analyzers for Silq can safely assume (instead of explicitly proving) temporary values are discarded safely. Third, Silq simulators may improve performance by dropping temporary values instead of explicitly simulating uncomputation. Finally, Silq’s key language features are relevant beyond Silq, as they can be incorporated into existing languages such as QWire or Q#.

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ProjectQ is an open-source software framework for quantum computing implemented in Python. It allows users to implement their quantum programs in Python using a powerful and intuitive syntax. ProjectQ can then translate these programs to any type of back-end, be it a simulator run on a classical computer or an actual quantum chip including the IBM Quantum Experience platform.   Other hardware platforms will be supported in the future.

The main features of ProjectQ are

• a high level language to write quantum programs
• a modular and customizable compiler
• various hardware and software back-ends
• a library (FermiLib) to solve fermionic problems on a quantum computer

Compiler

The compilation framework consists of a main compiler engine, which executes a user-defined sequence of compilation steps by sending the circuit through a chain of so-called compiler engines. Each compiler engine manipulates the circuit to, e.g., reduce the number of gates or quantum bits required to run the quantum program. Engines further down the stack become more back-end-specific and take care of the mapping of the logical circuit to the layout of the back-end.

Back-end

After the circuit has passed through all compiler engines, it gets sent to the back-end. The back-end may be actual quantum hardware, a simulator run on a classical computer, a circuit drawing engine, etc.

Having all of these possibilities in one unified framework allows users to test their implementations using a simulator before running them on actual hardware or getting resource estimates for larger instances.

ProjectQ is an open-source software framework for quantum computing implemented in Python. It allows users to implement their quantum programs in Python using a powerful and intuitive syntax.
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The following back-ends are available in the first version of ProjectQ:

Simulator –  Simulate your quantum programs locally with ProjectQ’s high-performance simulator.

Emulator– Check the correctness of your quantum algorithm by running it on our emulator which employs classical shortcuts wherever it can

IBM Quantum Experience – Run your quantum program directly on IBM’s 5-qubit quantum computer.

Resource Counter – Determine gate counts and the maximal width of your circuit.

Drawing Engine – Draw your quantum program as a customizable LaTeX circuit for publication.

Command Printer – Check the stream of commands which gets sent to the back-end or save a low-level representation of your quantum program.

CirqProjectQ

CirqProject Q is a port between ProjectQ and Cirq that provides two main functions.  First, it is a ProjectQ backend that converts a ProjectQ algorithm to a cirq.Circuit.  And second, it can decompose ProjectQ common gates to native Xmon gates that can be used to simulate a Google quantum computer with ProjectQ.

ProjectQ performance

ProjectQ has a high-performance simulator which allows simulating up to about 30 qubits on a regular laptop.  Using the emulation features of our simulator (fast classical shortcuts), one can easily emulate Shor’s algorithm for problem sizes for which a quantum computer would require above 50 qubits, see our example codes.

The advanced features of the simulator are also particularly useful to investigate algorithms for the simulation of quantum systems. For example, the simulator can evolve a quantum system in time (without Trotter errors) and it gives direct access to expectation values of Hamiltonians leading to extremely fast simulations of VQE type algorithms.

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Honeywell’s team of scientists, engineers and technicians has built the highest performing quantum computer available.

With a quantum volume of 64, the Honeywell quantum computer is twice as powerful as the next alternative in the industry. That means that the company is closer to industries leveraging our solutions to solve computational problems that are impractical to solve with traditional computers.

With a quantum volume of 64, the Honeywell quantum computer is twice as powerful as the next alternative in the industry.
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What makes Honeywell’s quantum computers so powerful is having the highest quality qubits, with the lowest error rates.  This is a combination of using identical, fully connected qubits and precision control.

What does a quantum computer look like?

First, there is an ultra-high vacuum chamber. It’s a stainless steel sphere, about the size of a basketball, with portals to allow in laser light, and from which the air has been pumped out such that it contains a vacuum of five times less particles than outer space. The chamber is cryogenically cooled with liquid helium to bring the temperature of the ion trap chip to 10 degrees above absolute zero (approximately negative 441 degrees Fahrenheit, colder than the surface temperature of Pluto).

Within the chamber, electric fields levitate individual atoms 0.1 mm above an ion trap, a silicon chip covered in gold about the size of a quarter. Scientists shine lasers at these positively charged atoms to perform quantum operations.

Meanwhile, there is a lot of equipment to control the quantum computer. Control systems are necessary to precisely manipulate the hundreds of independent electrical signals required to move the ions (qubits) in the intricate dance used for quantum information algorithms. Since the operations are all done with lasers, a multitude of optics are aligned across the optical tables, each specified for the correct color of light. All of this infrastructure takes up roughly two large optical tables (approximately 5 feet wide and 20 feet long), a significant space since the true computing power is harnessed with the few atoms hovering over the trap surface.

What will a quantum computer be used to solve?

Quantum computers harness their power by being able to investigate many potential outcomes at the same time.

Traditional computing bits are in a state of either “0” or “1.” On the other hand, Quantum bits, called qubits, can be in both states at the same time, a property called superposition.

That means that when you have these qubits interacting with each other in a computation, you get, what I call, a quantum superpower. There is an exponential expansion in the number of values that can all be considered at the same time.

Practically, that means that certain computations that can never be done on even the highest performing supercomputer will one day be computed on a quantum computer. One example is the best path of robots in a distribution center to improve speed of selecting items and packing orders (the best answer even supercomputers can’t find!).

Those computations are processed through algorithms designed and developed specifically for quantum computers. These algorithms are similar to classical algorithms from computer science, but also leverage a combination of physics and mathematics expertise. Within quantum’s ecosystem are a number of quantum-algorithm experts, who specialize in “converting” real world problems into quantum-standard algorithms. Honeywell Ventures has invested and partnered with two of the companies that do that, Zapata Computing and Cambridge Quantum Computing.

Future of quantum computing

When Honeywell set out to build a quantum computer, it prioritized creating the highest quality qubits, focusing on eliminating the errors present within the system on smaller numbers of qubits and then working to scale up the number of qubits.

Within quantum’s ecosystem are a number of quantum-algorithm experts, who specialize in “converting” real world problems into quantum-standard algorithms. Honeywell Ventures has invested and partnered with two of the companies that do…
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By having achieved such low errors on quantum operations, with each new qubit it add to the machine, the quantum volume expands. That increases the capability of quantum computing that we will be able to bring to our customers. And thanks to a partnership with Microsoft’s Azure Quantum, it will be able to offer organizations access to its quantum computer both directly through its interface as well as through the Azure Quantum portal.

Scientists and businesspeople hope quantum computers will one day be able to solve seemingly intractable mathematical problems. These range from enhanced modeling of chemical reactions, which could help people discover new drugs or develop more environmentally friendly fuels, to making machine learning techniques more efficient, among other benefits. Honeywell expects to boost its quantum computing power by a factor of 10 each year for the next five years.

When Honeywell set out to build a quantum computer, it prioritized creating the highest quality qubits, focusing on eliminating the errors present within the system on smaller numbers of qubits and then working to scale up the number of…
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About Honeywell

Honeywell International Inc. is an American company that is a publicly traded, multinational conglomerate. Honeywell is now headquartered in Charlotte, North Carolina, United States composed of four Business Groups—Aerospace, Building Technologies, Performance Materials & Technologies (PMT), and Safety & Productivity Solutions (SPS)—which produce aerospace systems, industrial products, and engineering services. Honeywell is a Fortune 100 company, and was ranked 77th in 2018. The company has a global workforce of approximately 110,000 workers with approximately 44,000 employed in the United States.

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Quantum++, simulator developed at softwareQ, is a modern C++11 general purpose quantum computing library, composed solely of template header files. Quantum++ is written in standard C++11 and has very low external dependencies, using only the Eigen 3 linear algebra header-only template library and, if available, the OpenMP multi-processing library. Quantum++ can simulate 25 qubits on a typical laptop and 30 or more on high performance servers. The platform is not restricted to qubit systems or specific quantum information processing tasks, being capable of emulating arbitrary quantum processes. It can even simulate noisy quantum processors, such as the ones available in current quantum hardware.

Software is not restricted to qubit systems or specific quantum information processing tasks, being capable of simulating arbitrary quantum processes. The main design factors taken in consideration were the ease of use, high portability, and high performance. The library’s simulation capabilities are only restricted by the amount of available physical memory. On a typical machine (Intel i5 8Gb RAM) Quantum++ can successfully simulate the evolution of 25 qubits in a pure state or of 12 qubits in a mixed state reasonably fast.

The simulator defines a large collection of (template) quantum computing related functions and a few useful classes. Most functions operate on such vectors/matrices passed by value and always return the result by value, without ever mutating their arguments. Collection of objects are implemented via the standard library container std::vector<>, instantiated accordingly.

The library is not restricted to specific quantum information tasks, but it is intended to be multi-purpose and capable of simulating arbitrary quantum processes. Other unique features of Quantum++ include the ability of simulating classical reversible networks up to billions of bits, strong multi-threading abilities, as well as built-in support for higher dimensional systems (qudits) that allows treating qubits and qudits on the same footing.

About softwareQ

softwareQ was incorporated in 2017 and is a private organization, started by founders Vlad Gheorghiu and Michele Mosca. The main products are a general-purpose high-performance quantum computing framework, Quantum++ and staq, a high-performance modular quantum computing processing toolkit. The company has  realized several of the first implementations of quantum algorithms including the Deutsch algorithm, quantum searching and approximate quantum cloning. softwareQ has developed methods and tools for the compilation and optimization of quantum circuits, such as T-gate optimization via matroid partitioning, number theory methods, quantum channel representations, coding theory methods, and parallel collision finding algorithms

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Riverlane is a research-led start-up that builds ground-breaking algorithms and software to unleash the predictive power of quantum computing.  The company started to deliver an operating system that allows the same quantum software to run on different types of quantum computing hardware. Its quantum operating system, Deltaflow.OS, will be installed on every quantum computer in the UK accelerating the commercialisation of the UK’s quantum computing sector. Deltaflow.OS is the flagship product of the company, along with Deltaflow-VL and Anian.

Deltaflow.OS

Deltaflow.OS is a radically new operating system for quantum computers. As hybrid systems, quantum computers contain classical and quantum computing elements which must be orchestrated to tease out optimal performance. This is crucial for near-term applications such as quantum chemistry. In the long term, quantum error correction requires close integration of quantum and classical compute. Deltaflow.OS exposes the different elements of the full quantum computing stack. This gives users the power to schedule tasks in an optimal way, improving the performance of quantum computers by orders of magnitude compared to other leading approaches.

Deltaflow-VL

Deltaflow-VL is an emulator of the control stack for quantum computers. Exposing the full control stack, it allows quantum programmers and algorithm developers to test and implement applications that require fast control such as error-correction and VQE-based algorithms. With Deltaflow-VL, Designers of quantum hardware can develop control system code away from the lab so they can fix bugs without worrying about down-time.

Anian

Anian is Riverlane’s application library in Deltaflow.OS. The tool is focussed on quantum chemistry and is being used to develop quantum chemical applications. Driven by the needs of end-users, Anian includes our patented algorithms that decrease quantum hardware requirements, such as the accelerated Variational Quantum Eigensolver. As Anian is connected to a realistic quantum hardware emulator, it allows users to test ideas without having to use quantum hardware. Users can also experiment with different ansätze, measurement strategies, noise models and algorithms.

About Riverlane

Riverlane is a research-led start-up that builds ground-breaking algorithms and software to unleash the predictive power of quantum computing. It was founded by Dr Steve Brierley, Senior Research Fellow in Applied Mathematics at the University of Cambridge. Backed by leading venture-capital funds and the University of Cambridge, company is developing new ways of making quantum computers accessible and commercially viable. Riverlane’s software leverages the capabilities of the quantum computer, which operates using the principles of quantum mechanics. In the same way that graphics processing units (GPUs) accelerate machine learning workloads, Riverlane uses quantum computers to accelerate the simulation of quantum systems.

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Zapata Computing, the leading enterprise software company for NISQ-based quantum applications, allows an Early Access Program to Orquestra(TM), its end-to-end platform for quantum-enabled workflows(TM). Orquestra enables advanced technology, R&D and academic teams to accelerate quantum solutions for complex computational problems in optimization, machine learning and simulation across a variety of industries.

Orquestra is agnostic across the entire software and hardware stack. It offers the most extensible library of open source and Zapata-created components for writing, manipulating and optimizing quantum circuits and running them across quantum computers, quantum simulators and classical computing resources. It comes equipped with a versatile workflow system and APIs to connect all modes of quantum devices. Its features:

• ^{Extensive Access to Quantum Libraries for Seamlessly Composing Workflows: With the most robust capabilities for quantum workflow design, execution and analysis, Orquestra users can begin with example workflows, open source algorithms, and a growing range of proprietary Zapata algorithms.}
• ^{Deployment Across NISQ, Quantum-Inspired and Multi-Cloud and Hybrid Cloud Classical Backends: Users can submit workflows to the Orquestra Quantum Engine (OQE) servers with command line tools and orchestrate workflow tasks across a full range of backends that include gate model devices (such as ion traps and superconducting), quantum annealers, quantum simulators and HPC resources.}
• ^{Moving Beyond Hardware-Agnostic into Hardware-Smart Development: Orquestra is the only quantum platform that goes beyond hardware-agnostic capabilities, allowing users to consider various devices’ strengths for particular problems and benchmark how workflows perform across devices.}
• ^{Scalable Orchestration: From managing complex data records to automated parallelization through container orchestration, quantum teams benefit from iterative, flexible experiments at scale.}
• ^{Multi-User Data Management and Interpretability: Quantum teams can swiftly record and compare results, then review and iterate as a multi-user team, incorporating benchmarking across quantum hardware and algorithms. Both intermediate data and final results can be exported into a Jupyter Notebook, Excel or Tableau for analysis.}

Users can also submit these workflows to the Orquestra Quantum Engine (OQE) servers with command-line tools and orchestrate workflow tasks across a variety of backends that include gate model devices, quantum annealers, quantum simulators, and HPC resources. Automated parallelization through container orchestration and management of complex records is offered as well.

About Zapata

Zapata Computing, Inc. is the quantum software company empowering enterprise teams to accelerate quantum solutions, innovation and transformation. With its introduction of Orquestra(TM), the first and only end-to-end, unified Quantum Operating Environment available today, Zapata is spearheading a new quantum development paradigm.

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Pasqal has been collaborating with Google to give access to its technology through Cirq, an open-source framework dedicated to the development and implementation of quantum algorithms on arbitrary platforms. Pasqal’s API is currently able to run instances on an emulator, while the first processor is being built.

Company’s developers and end-users are working on  exploring the capabilities of its architecture and prepare for the upcoming quantum advantage. Each approach to quantum computing (atoms, ions, photons, superconducting circuits) is based on different concepts with an impact on the software stack, from the physical qubit up to the application. Some parts of the software are specific to the underlying physics, which makes it challenging for software programmers to acquire familiarity and confidence to make the best implementation decisions, ideally regardless of the underlying  platform.Strong interactions are generated on demand between atoms brought into highly excited states called Rydberg states. These interactions can be switched on and off with 12 orders of magnitude extinction within a highly connected pattern, and are at the heart of analog simulation and digital gate-based computing with this state of matter.

Its processors are highly scalable and, thanks to high connectivity between qubits, make quantum acceleration for real life application a credible perspective.Employing Cirq it means that they are joining a large and growing eco-system. There are other eco-systems such as qiskit, pyquil and Q (Microsoft) for example.

About Pasqal

Pasqal founded with the vision to leverage the technology developed at Institut d’Optique in Palaiseau (France) to build quantum processors out of neutral atoms in their excited Rydberg state, ordered in large 2D arrays. Pasqal’s purpose is to bring practical quantum advantage to its customers. Pasqal is backed by Quantonation, an early stage venture capital fund focusing on Deep Physics and Quantum Technologies.

About Cirq

Cirq is an open-source framework for Noisy Intermediate Scale Quantum computers (NISQ). The Python based library allows writing, manipulating, and optimizing quantum circuits and running them on quantum computers and simulators.

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ISARA is a cybersecurity company specializing in creating production-ready quantum-safe security solutions for today’s computing ecosystems. As a commercial solution provider within a rich academic and research ecosystem, ISARA is part of a collaborative effort to raise awareness of quantum threats, and design and implement quantum-safe solutions that will work globally.

Radiate Quantum

ISARA Radiate Quantum-safe Toolkit is a high-performance, lightweight, standards-based quantum-safe software development kit, built for developers who want to test and integrate next-generation post-quantum cryptography into their commercial products.

Catalyst Agile Digital Certificate Technology

ISARA Catalyst Agile Digital Certificate Technology enables a seamless, cost-effective and simplified migration to quantum-safe security today to protect investments in durable connected devices and the Internet of Things (IoT) and complex public key infrastructures with no impact to end-users.

Catalyst OpenSSL Connector

ISARA Catalyst OpenSSL Connector allows easily integrate the ISARA Radiate Quantum-safe Toolkit’s cryptographic library of quantum-safe algorithms into your existing OpenSSL deployment.

Catalyst TLS Testbed

ISARA Catalyst TLS Testbed expands on TLS 1.2 to include agility in the form of hybrid key establishment, supported by a selection of ready-to-use classic and quantum-safe hybrid cipher suites allowing you to begin your migration to quantum-safe security today.

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The Atos Quantum Learning Machine emulate execution as a genuine, quantum computer world. Thanks to the bespoke software and hardware developed by Atos,  it has superior simulation capabilities, much more than any other affordable appliance: from 30 to 40 Qubits.

This appliance is composed of highly innovative elements:

• a scalable and large in-memory infrastructure
• an extensible data representation model (quantum circuit model)
• a quantum assembly programming language (based on universal QASM)
• a high level hybrid language (based on Python)

Atos Quantum Assembler (AQASM) is a core component of this appliance, enabling even to program new quantum gates or mix existing gates and accept quantum programs from others frameworks.

Atos Quantum program  was launched in November 2016 in order to prepare for the opportunities as well as the risks of quantum computing. As a result of this initiative, Atos was the first organization to offer a quantum noisy simulation module, the Atos QLM. Later  it launched myQLM, a free tool that allows a broader ecosystem to get acquainted with quantum programming and discover some features of the Atos QLM. 

Atos is a European multinational IT service and consulting company headquartered in France. It specialises in hi-tech transactional services, unified communications, cloud, big data and cybersecurity services. Atos operates worldwide under the brands Atos, Atos-Syntel, Atos Consulting, Atos Healthcare, Atos Worldgrid, Bull, Canopy and Unify.

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