Last week, NIST announced the approval of three post-quantum cryptographic algorithms that cannot be broken by a quantum computer. 

Here’s what leaders in the industry have been saying about this announcement and what it means for the future: 

Tim Hollebeek, industry and standards technical strategist at DigiCert:

“Today’s quantum computers are small and experimental, but they are rapidly becoming more capable, and it is only a matter of time before cryptographically-relevant quantum computers (CRQCs) arrive. These are quantum computers that are powerful enough to break the asymmetric cryptography used to protect communications and devices on the internet, and they could arrive in as little as 5-10 years. The good news is that the problem can be solved by switching to new hard math problems that are not vulnerable to quantum computers, and the new NIST standards describe in precise detail exactly how to use these new hard math problems to protect internet traffic in the future.”

Kristin Milchanowski Gilkes, global innovation quantum leader at Ernst & Young: 

“Since these requirements will be mandatory for federal agencies, and likely contracted partners, it is expected to be only a matter of time before mass adoption from commercial organizations. As quantum computers rapidly improve, the timelines by which they will be able to decode public-key cryptographic algorithms and in which organizations can upgrade to quantum-secure infrastructure are quickly overlapping. Business leaders should consider a risk-based approach as they evaluate their next steps and investments for quantum over the upcoming year.”

David Hook, VP of software engineering for Crypto Workshop at Keyfactor:

“Now that we finally have these published standards, organizations that are serious about safeguarding systems that involve the use of public key technology will need to start moving to deployment. Coupled with the application of crypto-agility, use of the new algorithms will be a necessary part of future-proofing public key infrastructure (PKI) systems to ensure long-term resiliency. PKI represents the cornerstone of systems that rely on secure digital identities and the exchange of encrypted data and these algorithms represent a major advance for supporting both areas.

That said, considering both the resource requirements, and the nature, of these algorithms, it does not mean the new arrivals are simply a case of ‘same-old, same-old.’ There will be a lot of work to do to make sure these algorithms can be used efficiently and effectively. Even without considering the government incentives to make use of post-quantum cryptography (PQC) algorithms now, organizations should be beginning their transition journeys. While the PQ does stand for post-quantum, anyone believing they can wait till after the arrival of a cryptographically relevant quantum computer, before worrying about PQC algorithm deployment, is making a terrible mistake.”

Tom Patterson, emerging technology security lead at Accenture:

“The NIST announcement on new global encryption standards for quantum marks a pivotal moment in our cybersecurity landscape. As quantum computers emerge, they present a significant risk to our current encryption methods. Organizations must assess their quantum risk, discover vulnerable encryption within their systems, and develop a resilient cryptographic architecture now.”

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“The official publication of these algorithms marks a crucial milestone to advancing the protection of the world’s encrypted data from cyberattacks that could be attempted through the unique power of quantum computers, which are rapidly progressing to cryptographic relevancy. This is the point at which quantum computers will harness enough computational power to break the encryption standards underlying most of the world’s data and infrastructure today,” IBM, who developed two of these new standards, wrote in a statement. 

RELATED: What NIST’s newly approved post-quantum algorithms mean for the future of cryptography

According to NIST, experts predict that we may reach that point of cryptographic relevancy within the next decade. This set of three new algorithms use different math problems that even a quantum computer would have trouble solving, NIST explained.

These new algorithms are part of NIST’s post-quantum cryptography (PQC) program, and today’s news comes eight years after NIST first announced a call for proposals asking for standards and strategies for securing information in a quantum world. 

“Quantum computing technology could become a force for solving many of society’s most intractable problems, and the new standards represent NIST’s commitment to ensuring it will not simultaneously disrupt our security,” said Laurie E. Locascio Under Secretary of Commerce for Standards and Technology and NIST Director. “These finalized standards are the capstone of NIST’s efforts to safeguard our confidential electronic information.”

NIST is also still evaluating two other sets of algorithms, and plans to select one or two of them by the end of the year. The first set contains algorithms with a different type of math problems than the selected one, and the second set contains algorithms that are designed for digital signatures.

In addition, NIST expects to announce 15 algorithms that it received during a second call for proposals in 2022. 

However, even though NIST is still approving additional algorithms, it says that they consider them as backups and recommends technologists not postpone using the three that have already been announced. 

“We need to be prepared in case of an attack that defeats the algorithms in these three standards, and we will continue working on backup plans to keep our data safe,” said Dustin Moody, a NIST mathematician who heads the PQC program. “But for most applications, these new standards are the main event.” 

Tom Patterson, emerging technology security lead at Accenture, believes that this announcement “marks a pivotal moment in our cybersecurity landscape. As quantum computers emerge, they present a significant risk to our current encryption methods. Organizations must assess their quantum risk, discover vulnerable encryption within their systems, and develop a resilient cryptographic architecture now.”

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Here, we’ll explore the foundations of quantum programming, draw comparisons to classical computing, delve into the role of quantum languages, and forecast the transformational impact of this nascent technology. Welcome to a beginner’s guide to quantum software – a journey to the heart of quantum computing.

Quantum vs. Classical Programming: The Core Differences

At its heart, the world of quantum computing contrasts starkly with that of classical computing. The differences extend beyond hardware to the very core of programming. Let’s illuminate some of the primary distinctions that delineate these parallel universes of computing.

Classical computers, the type most of us use daily, operate on binary data. This means they process information in “bits”, which are either in a state of 0 or 1. Classical programs, thus, revolve around manipulating these bits using logical operations.

Quantum computers, however, function quite differently. They leverage the quirks of quantum physics to process information via “qubits”. Unlike bits, a qubit can exist in multiple states simultaneously, thanks to a phenomenon called superposition. Additionally, qubits can also be entangled, meaning the state of one qubit can instantaneously affect the state of another, no matter the distance between them.

Therefore, programming a quantum computer necessitates a new approach, new logic, and an entirely new set of programming languages. Quantum software developers do not merely instruct a sequence of operations; they choreograph a dance of qubits, harnessing the peculiar properties of quantum physics to solve complex problems. The beauty of quantum programming lies in its ability to weave a ballet of superpositions and entanglements to achieve solutions exponentially faster than classical computing.

Quantum computing does not replace classical computing. Instead, it complements it, addressing problems that are currently unsolvable with classical computers due to the type of calculation and its complexity. Quantum software, therefore, requires a firm understanding of both classical and quantum principles to effectively leverage the strengths of each and navigate their respective challenges.

The Building Blocks of Quantum Programming

Quantum programming demands a unique set of terms to address the building blocks of a quantum program. These terms help us to describe and navigate the multi-dimensional universe of quantum computation. Here, we highlight three of these terms: quantum gates, quantum circuits, and quantum algorithms.

Quantum Gates: Much like classical computers use logical gates (AND, OR, NOT), quantum computers operate with quantum gates. But unlike their classical counterparts, quantum gates are reversible and deal with probabilities. They manipulate the state of qubits to perform quantum operations. A few examples include the Pauli-X, Pauli-Y, Pauli-Z, Hadamard, and CNOT gates.

Quantum Circuits: A sequence of quantum gates forms a quantum circuit. The quantum circuit defines the transformations that the qubits undergo to solve a given problem. However, the circuit’s behavior is inherently probabilistic due to the nature of quantum physics.

Quantum Algorithms: Quantum algorithms are sequences of quantum circuits designed to perform a specific task or solve a specific problem, much like a sequence of instructions forms a classical algorithm. Some popular quantum algorithms include Shor’s algorithm for factoring large numbers, and Grover’s algorithm for searching unsorted databases. Quantum algorithms exploit the phenomena of superposition and entanglement to outperform classical algorithms for certain problem types.

In the realm of quantum programming, we’re essentially designing a choreographed sequence that manipulates qubits through these quantum gates, forming quantum circuits to execute quantum algorithms. All this, to solve problems that classical machines find insurmountable.

The Quantum Programming Landscape

The world of quantum programming is as diverse as the set of problems it aims to solve. Various quantum programming languages and software platforms have emerged to address different needs, each with its unique approach and strengths. Here, we introduce you to this rich landscape.

Quantum Programming Languages: Just as classical computing has its C++, Python, and Java, quantum computing too has developed its languages. For example, Q# from Microsoft and Qiskit from IBM are two of the most popular quantum programming languages today. They allow you to define and manipulate quantum states, apply quantum gates, and measure the results.

Here we can see qiskit code that creates a quantum register with two qubits and applies a Hadamard gate to the first qubit and a CNOT gate to the two qubits. The code then measures the two qubits.

Software Platforms: Aside from standalone programming languages, there are software platforms designed to aid in quantum development. For instance, our platform at CLASSIQ provides an intuitive, visual way to design quantum circuits and algorithms. It is this high-level abstraction that allows quantum developers, beginners, and experts alike, to harness the power of quantum computing without getting bogged down in the low-level details of gate definitions.

Remember, each tool and language has its strengths, and the choice often depends on the problem you’re tackling. It’s about choosing the right tool for the right job, much like in the world of classical computing.

Quantum Programming Process

While programming a quantum computer can initially seem daunting, a high-level perspective simplifies the task into a series of logical steps. Here’s an overview of the general process:

Problem Formulation: The first step in quantum programming is defining the problem you want to solve. This might be optimizing a financial portfolio, simulating a chemical reaction, or breaking an encryption code. It’s crucial to understand that not all problems are suited for quantum solutions. Some tasks may be more efficiently handled by classical computers. Therefore, selecting the right kind of problem is a pivotal decision.

Algorithm Selection: Once you have defined the problem, the next step is to choose a quantum algorithm that can solve it. There is a growing library of quantum algorithms, each designed to address a particular type of problem. Some algorithms are well-suited for optimization tasks, while others are designed for simulation or machine learning.

Implementation: With the problem and algorithm in hand, you can now proceed to implementation. This is where quantum programming languages and platforms come into play. You translate the chosen algorithm into quantum code using your selected language or platform. This is often the most technical part of the process, and it can involve complex tasks like designing quantum circuits and managing quantum states.

Execution and Analysis: Finally, you execute your quantum program on a quantum computer or simulator and analyze the results. Since quantum computing is probabilistic, you may need to run your program multiple times to achieve a statistically significant result. The analysis often involves interpreting the quantum results in the context of your original problem.

Just like learning to program in a classical sense, the path to becoming proficient in quantum programming involves practice, patience, and a whole lot of curiosity.

The Future of Quantum Computing

The implications of quantum computing are broad and promising. As we refine our abilities to harness and manipulate quantum phenomena, we’ll witness quantum computers unlocking solutions to some of the world’s most complex and currently unsolvable problems. 

Innovation in Multiple Industries: Quantum computing has the potential to revolutionize various industries. Pharmaceutical companies, for example, could use quantum systems to simulate and analyze complex molecular structures, leading to new drug discoveries. The financial sector could leverage quantum algorithms for better risk assessment, portfolio optimization, and fraud detection.

Improved Data Security: The prospect of quantum computers breaking current encryption methods is a cause for concern, yet it also presents an opportunity. As we advance in quantum computing, we’ll simultaneously develop quantum-resistant encryption techniques, creating a new era of data security.

Scientific Discovery: Quantum computing promises to supercharge scientific discovery. In fields such as material science, quantum simulations can facilitate the discovery of new materials with desired properties. In climate science, it could offer more accurate climate predictions by better modeling complex systems.

While these exciting possibilities lie on the horizon, it’s important to remember that the quantum computing journey has just begun. It’s a field ripe for exploration and innovation.

As we transition from theory to practice, from abstraction to application, quantum programming will play an increasingly central role. By learning the principles of quantum programming today, you’re not only preparing for a quantum-powered future but actively participating in its creation.

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This approach enables organizations to adapt quickly to changes, making application and workflow automation deployment faster and easier. Additionally, Creatio Quantum introduces new components, generative AI, and a governance app, providing users with greater freedom in automation, the company explained.

With the introduction of Quantum, Creatio now fully embraces a composable approach, constructing all product functionality using pre-built components and blocks. At its most fundamental level, this consists of elements like widgets or sets of fields.

Creatio has disassembled all features of its CRM suite into components, blocks, and apps. This not only allows users to construct distinctive solutions using pre-made components and blocks but also enables them to utilize pre-built apps to meet their specific needs.

A highly sought-after feature, generative AI, has now been integrated into all of Creatio’s products, using models from OpenAI. According to Creatio, generative AI complements and expedites the no-code development process by automatically generating templates, components, or entire applications based on user-provided text input. This significantly reduces the time and effort required by no-code app creators to transform basic requirements into prototypes.

The launch of Quantum takes a further step in enabling businesses to adapt, create, and innovate with unparalleled efficiency, Creatio added.

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The SDK comes as a full quantum computer in simulation that can also interface with Intel’s quantum hardware, including Intel’s Horse Ridge II control chip and Intel’s spin qubit chip after it becomes available later this year.

The kit also features a programming interface written in C++ using a low-level virtual machine compiler toolchain. The company stated that because of this, Intel’s SDK provides interfacing with C/C++ and Python applications.

“The Intel Quantum SDK helps programmers get ready for future large-scale commercial quantum computers. It will not only help developers learn how to create quantum algorithms and applications in simulation, but it will also advance the industry by creating a community of developers that will accelerate the development of applications, so they are ready when Intel’s quantum hardware becomes available,” said Anne Matsuura, director of quantum applications and architecture at Intel Labs.

With version 1.0, developers also gain a quantum runtime environment to help them execute hybrid quantum-classical algorithms. 

The SDK also offers users the choice between two target backends for simulating qubits to either represent a higher number of generic qubits or Intel hardware. 

The first backend is Intel Quantum Simulator, an open-source, generic qubit simulator and the second is a target backend that simulates Intel quantum dot qubit hardware and enables compact model simulation of Intel silicon spin qubits.

Additionally, version 1.0 of the SDK allows developers to create a small workload in order to determine what functionalities are required from the quantum computer’s system architecture to efficiently and accurately run algorithms on qubits.

Lastly, the SDK is customizable and expandable, allowing for heightened flexibility when developing quantum applications.

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Version 2.0 enables users to save tests and reports on TestProject’s secure hybrid cloud and to benefit from zero server maintenance, end-to-end test creation, a collaborative testing repository, friendly dashboards and more, the company explained. Users can also save tests as local files directly on their machines with no cloud footprint and get a completely offline experience. 

“TestProject now aligns its free test automation platform to today’s various industry standards, accommodating its powerful capabilities for all and providing users the freedom to choose the option that works best for their organization’s restrictions,” TestProject stated in an announcement.

IBM Quantum Composer and IBM Quantum Lab announced
The two tools replace IBM Quantum Experience and include improvements into how users can manage files, receive notifications when jobs complete and view results. 

Users can search their files or view job results alongside the Jupyter notebook they are working on in IBM Quantum Lab. 

Meanwhile in IBM Quantum Composer, users can design and visualize circuits and the tool has an updated Setup and Run interface.

Sonatype acquires MuseDev
Sonatype announced that it is acquiring MuseDev, a startup that was incubated by Galois, Inc. 

MuseDev can install into any source control repo, automatically begin to analyze pull requests, and provide developers with accurate and actionable feedback.

MuseDev orchestrates 24 pre-configured code analyzers ranging from lightweight linters to deep static analysis tools and it can cover a wide variety of coding languages and bug types.

Additional details are available here.

Netlify announces Next.js integration
The integration enables users to install Next.js applications with zero configuration while having them fully integrated with the Netlify developer experience. 

This opens up many features for enterprise teams including role-based access, SAML single sign-on, two-factor authentication, integration with self-hosted GitLab and GitHub, and SOC 2 Type 2 attestation, the company explained.

Netlify also announced that it is developing a solution to effectively handle Incremental Static Regeneration (ISR) in Next.js. 

Docker announces new funding to help it focus on developers
Docker raised $23 million to capitalize on the accelerating demand for modern apps and to increase developer velocity. This round brings Docker’s total funding to $58 million. 

Docker’s collaborative application development platform accelerates software development from source code to cloud by simplifying developer workflows, providing trusted application components and integrating with leading developer tools 

“In the past year, applications have become paramount to not only all modern businesses but also as the primary means to connect society, all of which has greatly accelerated the need for developer velocity,” said Scott Johnston, the CEO of Docker. “This new investment, combined with our user and ARR growth momentum, validates Docker’s mission of helping developers and development teams bring their ideas to life by conquering the complexity of app development.” 

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“The transition to Public Preview of Azure Quantum is a key milestone for quantum computing and our ecosystem. This continues the momentum we saw last year, which includes selection for the National Quantum Initiative Quantum Research Centers, the addition of new Azure Quantum partners, and hardware advances in scaling control circuitry for qubits,” Krysta Svore, the general manager of Microsoft Quantum wrote in a blog post.

Users will have access to the open-source Quantum Development Kit (QDK) and the Q# programming language, which protects the developers’ investments by proactively anticipating and integrating with advances in quantum systems, according to Microsoft.

Azure Quantum also includes Microsoft’s new Quantum Intermediate Representation (QIR), which is a common open-source interface between different languages and quantum computing platforms. 

Since quantum computing is a rapidly growing and changing new field, Microsoft is helping new users with fundamental quantum concepts in Microsoft Learn, and offers self-paced tutorials in Katas.

Many samples on Microsoft’s website demonstrate how quantum computing can be implemented for various tasks such as moving quantum data with quantum teleportation, using the Q# standard libraries to implement a three-qubit bit-flip quantum error correction code, and calculating the path in a weighted graph with the smallest cost.

Users also have access to quantum computing and optimization resources from Microsoft’s hardware partners Honeywell Quantum Solutions and IonQ through a single development interface. 

Honeywell’s solution allows for mid-compute measurement and qubit reuse and IonQ’s system lets users run a two-qubit gate between any pair. Microsoft also encourages developers to help accelerate quantum computing research by developing optimization solutions based on solvers from Microsoft and 1QBit.

“Customers using Azure Quantum have already demonstrated valuable ways to build solutions to complex problems. From logistics and freight optimization to risk management solutions and fighting cancer, we’re seeing real-world application of Azure Quantum solutions today, and we are pleased to now expand Azure Quantum to Public Preview,” Svore added. 

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One track for this hackathon focuses on gate-based quantum computing division while the other is for quantum annealing. 

The hackathon will take place between January 30th and 31st online with an optional workshop on the properties and applications of NISQ devices as well as preparation for the hackathon taking place on January 29th. It is open to students at any level and non-faculty university affiliates. 

Additional details on the event are available here. 

Workato announces $110 million in funding for integration-led automation 
Integration-led automation provider Workato said that it will use the $110 million in new investment to ramp up its product innovation and technology development. The Series D funding round was led by global investment firm Altimeter Capital alongside Insight Partners.

“There’s been explosive growth in business apps and cloud technologies, but their potential remains largely untapped. This explosion has created tech chaos with siloed data, fragmented business processes and broken UX,” said Vijay Tella, the CEO and co-founder of Workato. “Workato addresses this with a single platform built for business and IT that easily, reliably, and securely connects their apps, data, and business processes so teams can work smarter and faster.”

Workato offers a no code/low code platform that combines integration and automation capabilities so that organizations don’t have to worry about melding together different robotic process automation (RPA), integration platform as a service (iPaaS), and business process management (BPM) solutions together. 

Veriton and Alteryx team up on unstructured data
The strategic partnership between Veritone and the analytic process automation platform Alteryx enables Alteryx’s customers to gain insight into unstructured data sources such as video, images, audio, and text. 

Veritone’s operating system for AI, aiWare, will be integrated into Alteryx’s platform and will be available for download from the Alteryx Gallery. 

The aiWare is capable of processing around four years-worth of unstructured video and audio-based data every day, according to Veritone. 

Additional details on possible use cases of the platform are available here.

New Google Smart Home App Discovery features 
Google introduced App Discovery and Deep Linking as two new convenience features that help users find Google-Assistant compatible devices and help with faster onboarding, according to Toni Klopfenstein, a developer advocate in a blog post.

Klopfenstein explained Google’s new App Discovery feature helps users find a smart home Action while Deep Linking enables developers to guide their app users to an account linking flow within the Google Home app. 

“Deep Linking and App Discovery can help you create a more streamlined onboarding experience for your users, driving increased engagement and user satisfaction, and can be implemented with minimal engineering work,” Klopfenstein added. 

Jellyfish announces $31.5 Million in funding to expand its engineering management platform
Jellyfish plans to use the Series B funding to “accelerate its mission of helping engineering leaders connect their team’s day-to-day operations to business priorities—elevating engineering leaders from executors to influencers of business strategy.”

The company saw a five-fold growth as engineering leaders sought to gain visibility into what their remote teams were doing to contribute value.

Jellyfish’s engineering management platform helps users analyze engineering signals and contextual business data to provide complete visibility. 

“Companies spend millions of dollars on engineering resources with little understanding of where it’s being spent or how resources are being allocated. Jellyfish is the clear leader in solving this, and we’re excited to partner with them as they seize this massive market opportunity,” said Matt Gatto, the managing director at Insight Partners, who will join the Jellyfish Board of Directors.

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The latest release extends the number of supported devices, simulators and development frameworks, enhances circuit optimization and noise mitigation techniques, and extends operating system support. 

t|ket> works across virtually all quantum hardware devices and quantum programming languages and can be easily migrated between devices by changing just a single line of code to connect devices across a developer’s research program.

New Google Play Console features
The two new features in the Google Play Console include a Publishing overview page that helps users better understand their publishing process and Managed publishing, which gives users better control of when their app updates go live on Google Play.

The new Publishing overview page displays all recent changes to your releases, store listings, and more, including those that are currently being reviewed or processed by Google Play. 

Meanwhile with Managed publishing, approved changes will only go live when users decide. 

Call for Code winner announced
The top prize for the competition went to Agrolly, an application to help the world’s small farmers cope with the environmental and business challenges of climate change.

Call for Code also introduced a new initiative—Call for Code for Racial Justice—to urge its international community of hundreds of thousands of developers to contribute to solutions to confront racial inequalities.

The 2020 Call for Code Global Challenge had asked developers to create solutions to help communities fight back against climate change and COVID-19. 

Cohesity and AWS team up on data management as a service (DMaaS)
The DMaaS solution is designed to provide enterprise and mid-size customers with a radically simple way to back up, secure, govern, and analyze their data, all managed directly by Cohesity and hosted on AWS.

“Cohesity and AWS are also focused on helping customers derive value from data. Through AWS, customers can access a wealth of AWS services, including Amazon Macie, to help customers meet compliance needs, and Amazon Redshift for analytics. We are thrilled to collaborate with AWS and look forward to ushering in a new era in data management for customers globally,” said Mohit Aron, the CEO and founder of Cohesity.

The solution provides a comprehensive set of data management services, advanced security and ransomware detection, sophisticated cloud-based services that derive additional value from data, and more. 

Couchbase Lite and Couchbase Sync Gateway 2.8
The release’s new functionality enables secure data sync from cloud to edge and directly between edge devices, guarantees applications are always available and responsive in real time.

The new replication capability in Couchbase Sync Gateway 2.8, in combination with Couchbase Lite 2.8 and Couchbase Server, supports the distributed cloud model at every tier — from the cloud to the edge —  securely synchronizing data between web, mobile, and IoT apps and the backend database as well as between cloud and edge data centers.

Additional details are available here.

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