Category Archives: Quantum Computing

Quantum networks hold enormous potential for groundbreaking advances in many areas of science and technology. Once this technology matures, it is expected to be an essential component of quantum computing. It could have the equivalent impact as the internet has had on digital communication.

The U.S. Department of Energy (DOE) has announced that three collaborative projects in quantum networking will receive $24 million for up to three years. The DOEs Argonne National Laboratory will be participating in two of the projects and leading one of them, InterQnet. Anticipated funding for InterQnet is $9 million over three years.

Quantum networks would lead to breakthroughs in quantum computing by linking multiple quantum computers to greatly boost computational power. This technology could also advance precision measurements based on quantum principles that would otherwise not be possible. And it could pave the way for new applications yet to be conceived.

Our results will serve as the bedrock for scaling up quantum networks to connect quantum devices around the nation. Rajkumar Kettimuthu, computer scientist

The InterQnet project will address multiple challenges with scaling up quantum networks from the current metropolitan scale to much longer distances and more complex architectures. To that end, Argonne is collaborating with DOEs Fermi National Accelerator Laboratory (Fermilab), Northwestern University, the University of Chicago and the University of Illinois Urbana-Champaign.

The quantum processes involved govern the behavior of elementary particles, such as photons, which are the fundamental constituents of light. The key process is called entanglement. Two entangled particles are interdependent even after they are separated over vast distances.

What fascinates me about quantum networks is that they can transport information in a fundamentally new way, said Rajkumar Kettimuthu, a computer scientist at Argonne and principal investigator for InterQnet. They allow you to communicate quantum information from one point to another in a network by leveraging quantum entanglement while also transmitting classical information; this is different from transmitting the quantum information over a communication medium, such as a fiber-optic cable, or free space.

He furtherexplained that because entanglement-based quantum communication requires transmittal of classical information from source to destination, you cannot communicate quantum information faster than light.

We have already demonstrated quantum communication with entangled photon pairs in a laboratory, between buildings at Argonne, and between Argonne and Fermilab, Kettimuthu said.

InterQnet will be showcasing quantum communication across five buildings on the Argonne campus with multiple distinct quantum platforms and an early-stage quantum repeater. Each platform will use a different type of quantum bit (qubit), the basic unit of information in quantum information. Unlike classical bits, which can only be either 0 or 1, a qubit can simultaneously represent a combination of both states. This characteristic is one reason quantum computers possess vastly superior computational capabilities for some applications.

Argonne researchers previously collaborated in the development of four types of qubits: electrons, ytterbium atoms, charged erbium atoms (ions) and microwave circuits. A significant milestone would be to demonstrate the Argonne quantum network connecting these distinct qubit platforms. One of them would serve as a quantum repeater, an essential network element to extend the communication distance.

Our results will serve as the bedrock for scaling up quantum networks to connect quantum devices around the nation, Kettimuthu said. The team will complement practical experiments with computer simulations to determine the optimal architecture for a futuristic quantum network scalable to great distances.

This new project grew out of work done in various earlier and ongoing projects. These include several Argonne Laboratory Directed Research and Development projects; the Illinois Express Quantum Network (IEQNET) led by Fermilab; and Q-NEXT, a DOE Office of Science national quantum information science (QIS) center led by Argonne.

InterQnet will also leverage various existing QIS hardware and software elements already in place. These include the fiber-optics connection between Argonne and partner institutions and a quantum network simulator developed at Argonne.

Fermilab has been awarded DOE funding for a separate project, Advanced Quantum Network for Scientific Discovery. This Fermilab-led project will leverage the expertise and capabilities developed by IEQNET. The objective is to improve the transmission of information over quantum networks. Collaboration between the two national labs will continue as Argonne will also participate in the project along with other partners.

Quantum networks are the foundation for distributed and scaled-up quantum computing, which has potential applications in banking, national security, energy delivery infrastructure, information security and many others, said Panagiotis Spentzouris, associate laboratory director for emerging technologies at Fermilab.

The DOE Advanced Scientific Computing Research program is funding this research.

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Argonne to receive new funding to develop quantum networks - Argonne National Laboratory

Worldwide efforts are ongoing to scale up from hundreds to millions of qubits. Common challenges include well-controlled qubit integration in large-size wafer facilities and the need for electronics to interface with the growing number of qubits.

Superconducting quantum circuits have emerged as arguably the most developed platform. The energy states of superconducting qubits are relatively easy to control, and researchers have been able to couple more than a hundred qubits together.

This enables an ever-higher level of entanglement one of the pillars of quantum computing. Also, superconducting qubits with long coherence times (up to several 100s) and sufficiently high gate fidelities two important benchmarks for quantum computation have been demonstrated in lab environments worldwide.

In 2022, imec researchers achieved a significant milestone towards realizing a 300mm CMOS process for fabricating high-quality superconducting qubits. Showing that high-performing qubit fabrication is compatible with industrial processes addresses the first fundamental barrier to upscaling, i.e., improved variability and yield. Among the remaining challenges is the need to develop scalable instrumentation to interfacewith the growing number of noise-sensitive superconducting qubits.

In the longer term, much is expected from Si-spin-based qubits. Si spin qubits are more challenging to control than superconducting qubits, but they are significantly smaller (nm size vs. mm size) giving an advantage for upscaling.

Also, the technology is highly compatible with CMOS manufacturing technologies, offering wafer-scale uniformity with advanced back-end-of-line interconnection of the Si quantum dot structures.

However, Si-based quantum dot structures fabricated with industrial manufacturing techniques typically exhibit a higher charge noise. Their small physical size also makes the qubit-to-qubit and qubit-to-classical control interconnection more challenging.

The much-needed increase in qubits requires versatile and scalable solutions to control them and read out meaningful results. In early quantum processors today, external electronics circuits are used with at least one control line per qubit running from the room-temperature stage to the lowest temperature stage of the dilution refrigerator that holds the qubits.

This base temperature is as low as ten milliKelvin (mK) for superconducting quantum computing systems. Such an approach can be used for up to a few thousand qubits but cannot be sustained for large-scale quantum computers that require dynamic circuit operations such as quantum error correction.

Not only do the control and readout lines contribute to a massive I/O bottleneck at the level of the dilution refrigerator, but each wire also brings in heat to the cryogenic system with no budget left to cool them.

An attractive solution is to use CMOS-based cryo-electronics that hold RF (de-) multiplexing elements operating at the base temperature of the dilution refrigerator. Such a solution alleviates the I/O bottleneck as the number of wires that go from room to mK temperatures can be significantly reduced.

For the readout, for example, the multiplexers would allow multiple signals from a group of quantum devices to be switched to a common output line at the dilution refrigerator base temperature before leaving the fridge.

This approach has already been demonstrated for Si spin qubit quantum systems. However, thus far, the cryogenics electronics have not been interfaced with superconducting qubits due to their significantly lower tolerance to high-frequency electromagnetic noise. Be it in the form of dissipated heat or electromagnetic radiation, noise can easily disrupt fragile quantum superpositions and lead to errors.

Thats why the power consumption of the multiplexing circuits should be very low, well below the cooling budget of the dilution refrigerator. In addition, the multiplexers must have good RF performance, in terms of, for example, wideband operation and nanosecond scale switching.

Imec has demonstrated an ultralow power cryo-CMOS multiplexer for the first time that can operate at a record low temperature of 10mK. Being sufficiently low in noise and power dissipation, the multiplexer was successfully interfaced with high-coherence superconducting qubits to perform qubit control with single qubit gate fidelities above 99.9%.

This number quantifies the difference in operation between an ideal gate and the corresponding physical gate in quantum hardware. It is above the threshold for starting experiments like quantum error correction a prerequisite for realizing practical quantum computers that can provide fault-tolerant results. The results have been published in Nature Electronics [1].

The multiplexer chip is custom designed at imec and fabricated in a commercial foundry using a 28nm bulk CMOS fabrication technology. Record-low static power consumption of 0.6W (at a bias voltage (Vdd) of 0.7V) was achieved by eliminating or modifying the most power-hungry parts of a conventional multiplexer circuit as much as possible.

The easiest way to run the multiplexer is in static operation mode, which is very useful for performing single qubit characterizations. However, operations involving more than one qubit such as quantum error correction or large-scale qubit control will require a different approach allowing concurrent control of multiple qubits within a pulse sequence.

Imec researchers developed an innovative solution involving time division multiplexing of the control signals. This could provide an interesting basis for building future large-scale quantum computing system architectures.

Preliminary experiments show that the multiplexer can perform nanosecond-scale fast dynamic switching operations and is hence capable of doing active time division multiplexing while signal crosstalk is sufficiently suppressed. Currently, the team is working towards implementing a two-qubit gate based on the concept of time division multiplexing.

The experiments described in this work have been set up to contribute to developing large-scale quantum computers by reducing wiring resources. But they also bring innovations to the field of metrology.

Throughout the experiments, the ultralow noise performance of the multiplexing circuit at mK temperature was characterized for the first time using imecs superconducting qubits. In other words, the superconducting qubit can be used as a highly sensitive noise sensor, able to measure the performance of electronics that operate at ultralow temperatures and noise regimes that have never been explored before.

Figure 1 Routing microwave signals using cryo-multiplexers. a, Standard RF signal routing for measuring superconducting qubits in a dilution refrigerator. b, Scheme for multiplexing the control and readout signals at the base-temperature stage of a superconducting quantum computer. The required RF signals can be generated from either room-temperature electronics outside the dilution refrigerator or cryo-electronics operating inside. c, Schematic representation of the cryo-CMOS multiplexer. d, Optical image of the PCB onto which the cryo-CMOS multiplexer is wire bonded. e, Optical micrograph of the cryo-CMOS multiplexer chip (as published in Nature Electronics).

Si spin qubits are defined by semiconductor quantum dot structures that trap a single spin of an electron or hole. For optimal spin qubit control, the qubit environment must display low charge noise, the gate electrodes must be well-defined with small spacings for electrical tunability, and the spin control structure must be optimized for fast driving with lower dephasing.

High-fidelity Si spin qubits have been repeatedly demonstrated in lab environments in the few-qubit regime. Techniques for processing the qubit nanostructures, such as metal lift-off, are carefully chosen to achieve low noise around the qubit environment.

But these well-controlled fabrication techniques have a serious downside: they challenge a further upscaling towards larger numbers of qubits, as they cannot offer the required large-scale uniformity the very reason these methods were abandoned decades ago in the semiconductor industry at large.

Industrial manufacturing techniques like subtractive etch and lithography-based patterning, on the other hand, can offer wafer-scale uniformity, paving the way to technology upscaling. But they have been observed to degrade the qubit environment easily.

Additionally, qubit devices, like the closely spaced gate electrode and the spin control structures, arent regular transistor structures either and therefore deviate from the typical transistor roadmaps, requiring (costly) new development.

To make the device optimization more complex, the qubit performance depends largely on all these structures and on comprehensive optimizations of the full gate stack, metal electrode design, and spin control modules that are necessary for qubit performance.

Nevertheless, the overall device structure should still be compatible with the fabrication methods used for advanced, scaled transistors in commercial foundries to ensure a fair chance at upscaling.

At imec, researchers are tackling this conundrum through careful optimization and engineering of the fab qubit in a modular approach: different qubit elements are separately addressed and optimized as part of a state-of-the-art 300mm integration flow, ensuring forward compatibility with scaling requirements while satisfying the need for dedicated, non-standard device optimization as required by the challenging quantum environment.

Preliminary results on optimised structures look promising, highlighting 300mm fab integration as a compelling material platform for enabling high-quality Si-based spin qubits and upscaling studies.

The developments take advantage of the unrivalled uniformity offered by CMOS manufacturing techniques.

Figure 2 Si spin qubits manufactured with state-of-the-art 300mm integration flows.

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Imec reports on quantum computing progress - Electronics Weekly

The University of Calgary and Xanadu, a leading quantum computing company, announce a new partnership to provide educational materials and support for UCalgarys thriving quantum ecosystem. Through this partnership, UCalgary and Xanadu aim to help students become confident and quantum-ready professionals prepared to contribute to Canadas growing quantum workforce.

UCalgary stands out for its entrepreneurial approach to quantum research and development, fostering student empowerment through leadership and participation in initiatives like the Institute for Quantum Science and Technology (IQST), Quantum City, and the Quantum Horizons Alberta initiative.

Moreover, the Faculty of Science is set to launch the Professional Master of Quantum Computing program in January 2024. This program is designed to provide students with the skills to understand and support quantum computing systems in practical settings, as well as gain practical experience through use cases and experiential learning.

To ensure students enrolled in the Professional Master of Quantum Computing program have access to cutting-edge quantum hardware and software, UCalgary has selected Xanadu, a Toronto-based company, as its inaugural official partner for support. Together, UCalgary and Xanadu will advance quantum computing education by integrating hands-on learning resources developed by Xanadu into existing courses at UCalgary.

This collaboration aims to generate a pipeline of highly skilled professionals in quantum computing. An illustration of this collaborative partnership in action can be seen in Xanadus participation in the upcoming qConnect 2023, which is co-hosted by Quantum City in November and focuses on connecting quantum creators and users.

Xanadu (follow on X @XanaduAI) is on a mission to build quantum computers that are useful and available to people everywhere. Since 2016, they have been building cutting-edge photonic quantum computers and making remarkable progress in the field, such as being one of three teams worldwide to achieve quantum computational advantage.

In addition to their hardware success, Xanadu leads the development of multiple open-source software libraries that have been the core of several research projects. Most notable of these libraries is PennyLane,an open-source software framework for quantum machine learning, quantum chemistry, and quantum computing with the ability to run on all hardware. Check out the PennyLane demos,a gallery of hands-on quantum computing content.

Fariba Hosseinynejad Khaledy

Using Xanadus quantum computers and software libraries like PennyLane, UCalgary and Xanadu will enable students to conduct research and develop new software applications while receiving dedicated training and custom-built educational tools to support their quantum journeys.

Dr. David Feder, PhD, associate professor at IQST has been instrumental in initiating and facilitating this partnership and supervises students like Fariba Hosseinynejad Khaledy. Khaledy is a current graduate student involved in a collaborative project between Feder and researchers from Xanadu.

She explains how the access to these resources allow her to continue her science career: I am thrilled to be a part of a project that not only aligns with my research interests but also holds the potential to transform our work into real-world applications. The prospect of contributing to this initiative with the resources that Xanadu provides is undeniably exciting. I firmly believe it's crucial for graduate students to embrace this perspective early in their studies and consider aligning their projects with industry trends and demands.

The collaboration between UCalgary and Xanadu will enhance UCalgarys new Professional Masters of Quantum Computing program and is a testament to the ecosystem building the Quantum City initiative is generating at the university and, more broadly, in Alberta.

Its fantastic to be partnering with UCalgary in this initiative to make top-tier quantum computing education more accessible to students. Its exciting to see top universities like UCalgary put in the work to support their students in the exploration of this exciting and promising field, says Jen Dodd, quantum community team lead at Xanadu.

Dr. Rob Thompson, associate vice-president (research) and director of research services at UCalgary,says, The field of quantum computing is growing rapidly, and we are committed to delivering the best quantum computing education, while also building an ecosystem for quantum science and technology in Alberta, through Quantum City.

Xanadus achievements coupled with a team that is dedicated to sharing their knowledge and building a better quantum community made them a clear choice to partner with in this exciting initiative at UCalgary.

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UCalgary to provide hands-on quantum computing opportunities ... - University of Calgary

More swiftly than ever, quantum computing is evolving, which is a powerful reminder that the technology is rapidly moving toward being commercially useful. For instance, a Japanese research institution recently disclosed progress in entangling qubits that could improve quantum error correction and possibly open the door for massively parallel quantum computers.

Quantum computing startups are booming as technology advances and investment surges. Major technological firms are also advancing their quantum capabilities; firms like Alibaba, Amazon, IBM, Google, and Microsoft have already started offering for-profit quantum computing services.

In the current tech world, quantum computing is fit for certain algorithms like optimization, machine learning, and simulation. With the advent of such algorithms in quantum engineering, several use cases can be applied in diverse fields. Starting from finance, fraud detection, healthcare, supply chain management, chemicals, petroleum, and researching new materials are the areas that can have a primary impact.

This article will go into the details of the use cases of quantum computing. But first, let us look at the quantum computing meaning and explore the market overview of quantum computing technology. Lets start learning!

In the cutting-edge science of quantum computing, data is processed uniquely using concepts from quantum physics. Unlike classical computers, which utilize bits as the basic unit of data (0 or 1), quantum computers use quantum bits, also called qubits. Superposition, a characteristic of qubits that allows them to exist in numerous states concurrently, will enable them to do complex calculations at exponentially quicker rates for specialized jobs.

Innumerable fields, including materials science, artificial intelligence, and encryption, benefit greatly from quantum computing. Researchers and businesses worldwide are attempting to harness its potential and surpass huge technological obstacles, but it is still in its infancy.

One of the latest technology trends that has become widely adopted is quantum computing. A standard processor cannot build effective models to solve complicated issues with regular processing capacity because of the volume of data that businesses collectfor example, finding the greatest prime number to use in encryption.

Lets move ahead to witness the growing quantum computing market before moving to understand the use cases of quantum computing.

Let us explore the transformative benefits and potential uses of quantum computing. Discover the remarkable benefits that quantum engineering offers across diverse fields, from revolutionizing cryptography and accelerating drug discovery to supercharging artificial intelligence and addressing complex optimization problems.

Quantum computing can dramatically improve the process and provide numerous benefits in chemical simulation.

Scientists could use this increased computational power to investigate larger and more complex molecular structures, allowing them to achieve more accurate and detailed simulations of chemical systems due to the exponential complexity of the quantum world, which classical computers have difficulty simulating accurately.

A variety of approaches with differing degrees of accuracy and computational expense are used in quantum chemical simulations. Here are three examples:

Route planning and logistics are also changing due to quantum technology. By providing global routing optimization and regular re-optimizations, the use of quantum computers might drastically lower the cost of freight transportation and increase customer satisfaction.

The Quantum Approximate Optimization Algorithm (QAOA) is one of the most well-known algorithms in quantum optimization. QAOA combines traditional optimization methods with quantum computing to approximate solutions to optimization issues.

Another method that uses quantum fluctuations to locate ideal solutions at low energy levels is known as quantum annealing (QA). Applications of QA that are particularly helpful include the Quadratic Unconstrained Binary Optimization (QUBO) issue and the well-known NP-hard Ising model.

The potential role of quantum computing and AI in developing next-generation artificial intelligence (AI) is also significant. At the same time, it is still debatable whether QML will have any advantages, especially in light of the release of ChatGPT late last year.

For the status quo machine learning (ML) evolving in 2021, which is frequently constrained by a limited scope, an inability to adapt to new scenarios, and a lack of generalization skills, the capacity to handle complexity and keep alternatives open is a clear advantage. Artificial general intelligence (AGI) development may be made possible by a quantum computer, while some consider this the greatest risk.

Now that we have understood the benefits, lets move to learn the quantum computing use cases.

While we anticipate quantum advantage to be a reality by 2025, we assist businesses in identifying immediate and longer-term opportunities. Additionally, it goes beyond the uses of quantum computing for business. We also find applications that have significant potential for societal impact.

Several of the more intriguing use cases of quantum computing applications include:

Quantum computers can bring in $2 to $5 billion in operating revenue for financial institutions over the next ten years, coupled with quantum-inspired algorithms running on classical computers. The ability to handle uncertainty in decision-making more effectively is one of the primary benefits of quantum technology for financial actors. Applications include, among others, asset pricing, risk analysis, portfolio optimization, fraud detection, and capital allocation.

The ability of quantum technologies to perform multiple calculations at once makes them particularly well suited to issues that call for simulating situations with various distinct variables or selecting the best course of action from among several possibilities. This applies to a variety of financial sector quantum computing uses.

For instance, Spanish bank BBVA and quantum company Multiverse Computing have teamed up to optimize investment portfolios. The need to account for the effects of numerous external factors on the performance of assets is a well-known issue in finance. The test demonstrated that Multiverse's quantum-inspired computing techniques accelerated the process and could maximize profitability while minimizing risk.

Options pricing is another use in finance. The Swiss startup TerraQuantum is collaborating with the financial services firm Cirdan Capital to price a difficult class of "exotic options" using quantum-inspired algorithms. Typically, this is done using mathematical operations based on market simulations. According to the business, the first data indicate a 75% boost in pricing speed compared to conventional approaches.

Financial organizations are also looking at quantum computing to improve credit risk analysis. French startup PASQAL and Multiverse are working on a quantum approach for French bank Crdit Agricole to anticipate better credit rating downgrades in borrowers. Classical methods already exist for this problem but can't process the particularities of individual situations. The bank expects factorization in quantum computing use cases and algorithms to improve the efficiency of the process.

Pharmaceutical companies can screen bigger and more complicated molecules with quantum computing, map interactions between a medicine and its target more accurately, and accelerate the development process at a lower cost. Better immunizations, treatments, and diagnostics will be available sooner and more effectively.

To create a medicine, one must first choose the appropriate drug targetthe protein, DNA, or RNA in the body responsible for a specific diseaseand then create the chemical that will safely and efficiently affect that target. Finding the perfect combination is an expensive, time-consuming procedure still largely based on trial and error due to the infinite number of potential targets and compounds.

Qubit Pharmaceuticals, a startup based in Paris, builds digital twins of medicinal compounds using hybrid quantum algorithms. These quantum-based models can simulate how molecules interact with other components and anticipate behavior accurately since they can represent many chemical features. This eliminates the need to synthesize molecules, allowing scientists to create and examine molecules digitally. According to the business, the technique may cut the time needed to screen and choose prospective medication candidates in half and reduce the required investment by 10.

Weather forecasts are notoriously inaccurate because they rely on simulations using data from current weather conditions. A model far too vast for a conventional computer would be needed to accurately represent hundreds of parameters and analyze how they interact to predict the weather more precisely.

The capacity of quantum computers to consider a wide range of parameters may change the game. For instance, the German chemical company BASF is implementing PASQAL's technology into its weather-modelling applications to gain a quantum edge over traditional methods.

Enhancing battery design entails creating a new generation of more reliable, secure, and affordable gadgets. The main challenge is identifying the precise factors resulting in an improved material, like medication design.

The construction of more effective batteries may be made possible by quantum computers' ability to precisely model chemical processes at the atomic level, according to Finnish quantum firm IQM, which raised 128 million last year for its climate-focused technology. Phasecraft claims that quantum computers could more quickly model battery materials than current technology.

Delivering electricity to the network is a difficult and time-consuming task that involves precise synchronization and coordination of a massive network of sensors, communication infrastructure, data management systems, and control mechanisms. To complete this operation more quickly, quantum computers are a good choice.

Iberdrola, a Spanish utility firm, and Multiverse have teamed up to examine how quantum algorithms might improve the operation of power networks. The project's diverse use cases call for assessing various possible combinations. For instance, the company expects using quantum algorithms to make choosing the best places for batteries within an electrical network easier.

Numerous variables can affect how long it takes to go from point A to point B. To find the best way, quantum algorithms are being created to calculate how every route and every factor might affect one another.

For instance, the French startup Quandela is collaborating with the global corporation Thales to develop a quantum algorithm that might improve drone traffic. Thales predicts that conventional computers won't be able to consider all the factors that affect trajectory shortly as the number of drones operating in populated areas rises. These range from the technical flight limitations of drones to avoiding drone-drone collisions, taking into account the locations where drones are prohibited, and preserving battery life. Quantum algorithms might model all of these elements to identify the best route for each drone.

Predicting and identifying defective parts in production lines has great economic value for manufacturing. Still, it is difficult due to the massive amount of data that must be accounted for to generate such predictions. Multiverse and Bosch are working together to create digital twins that simulate the industrial line, predict where supply chains may break, and optimize when and where maintenance is required.

Similarly, PASQAL and BMW have collaborated to deploy quantum algorithms that can replicate the production of metallic pieces to detect faults and ensure that parts meet standards.

Molecular modeling enables breakthroughs such as more efficient lithium batteries. Quantum computing will allow us to model atomic interactions at much finer and greater scales. New materials can be employed in several quantum applications, including consumer goods, automobiles, and batteries. Without approximations, quantum computing will enable molecular orbit calculations.

A greater knowledge of the interactions between atoms and molecules will allow for the development of novel medications. Detailed DNA sequence analysis will aid in detecting cancer at an early stage by establishing models that will determine how diseases evolve.

Quantum technology will have the benefit of allowing for a scale-dependent, in-depth analysis of molecular behavior. Chemical simulations will enable the development of novel drugs or improve protein structure predictions, scenario simulations can improve the ability to predict the likelihood that a disease will spread or its risks, the solution of optimization problems will improve drug distribution chains, and finally, the application of AI will hasten diagnosis and provide more accurate genetic data analysis.

New methods for combating climate change can be made possible by quantum computing. Modeling molecular interactions involving 50 to 150 atoms, which classical computers cannot handle, is one of the early uses. Better and more effective chemical catalysts may be created, leading to lower emissions and more effective carbon capture and storage techniques. In the future, quantum technology might aid in creating stronger and lighter building materials for automobiles and aircraft.

The field of artificial intelligence (AI), which fundamentally alters how businesses run, presents both fresh chances for advancement and difficulties. According to the artificial intelligence guide, the power of AI to interpret and analyze data has significantly improved. Due to the complexity of workflows and the increasing amount of data that needs to be processed, AI is also computationally demanding.

We may be able to solve complicated issues that were previously intractable thanks to machine learning and quantum computing, which can also speed up processes like model training and pattern recognition. The three types of computing that will predominate in the future are classical, biologically inspired, and quantum.

The development of quantum machine learning algorithms like the Quantum-enhanced Support Vector Machine (QSVM), QSVM multiclass classification, variational quantum classifier, or qGANs has received a lot of attention in recent years because of the intersection of quantum computing and machine learning.

Let us dive into the example of a use case in quantum computing.

These are some of the most popular software platforms, but many more software platforms and libraries are being developed and utilized in quantum computing.

Quantum computers, in some ways, are transforming the world right now. First, engineering breakthroughs are announced regularly. ColdQuanta, for example, uses lasers to ultracool atoms to nanoKelvins or degrees above absolute zero to use as qubits. And that's just one illustration of how the quantum computing industry's engineering discoveries will help the planet.

Second, quantum physics is moving from theory to experiment. Using ColdQuanta as an example, physicists worldwide can create and experiment with Bose-Einstein Condensates (BEC), often known as "quantum matter," through their cloud-accessible Albert system. While Albert is not a quantum computer, its younger relative Hilbert will also use ultracold atom technologies.

Furthermore, computer science is progressing rapidly. Since Ewin Tang set the bar with recommendation systems, scientists have been motivated to speed up conventional algorithms using quantum algorithms. This quantum-inspired technique provides immediate benefits because classical algorithms can be implemented today. As it was following Ewin Tang's breakthrough, the challenge now is to create even more powerful quantum algorithms.

Finally, quantum computers are significantly less harmful to the environment than supercomputers. That estimate, by the way, includes the adoption of extreme refrigeration and all of the associated power consumption. However, certain qubit technologies work at ambient temperature and can eliminate the need for a dilution chiller, lowering energy use even more.

Quantum computers will not replace personal computers. Since it is more efficient, numerous programs will continue functioning on current devices. However, quantum computing applications go far beyond number factoring and unstructured search. In reality, the future of quantum computing appears to be good for almost everyone.

Despite recent significant advancements in the development of quantum computing hardware and algorithms, the technology still has few practical applications. Nevertheless, the use cases presented are sufficient evidence of the potential that quantum computing (or quantum mechanics) can offer us.

But as quantum computing technologies develop, more real-world applications will probably follow. But for now, we can only monitor the market and wait for well-researched use cases from some of the world's top businesses, research organizations, and people. Only then will we witness how quantum computing applications may improve our lives.

Aparna is a growth specialist with handsful knowledge in business development. She values marketing as key a driver for sales, keeping up with the latest in the Mobile App industry. Her getting things done attitude makes her a magnet for the trickiest of tasks. In free times, which are few and far between, you can catch up with her at a game of Fussball.

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Quantum Computing Use Cases Are Getting Real: What You Need To Know - MobileAppDaily

Are you ready for the future? A future where calculation time drops from days to seconds, and information is processed in an entirely different way. A future where quantum computing, once a theoretical model for computing based on quantum phenomena, becomes a widespread technological reality and a commercial opportunity.

Unlike classical computers that use bits (0s and 1s) to process information, quantum computers use quantum bits or qubits, which can exist in multiple states simultaneously due to superposition. This allows quantum computers to handle vast amounts of data and perform computations in parallel.

As of now, innovators around the world are exploring various applications for these powerful machines. Quantum technology startups are multiplying and investors are taking notice:

What transistors did for the rapid advancement of electronic devices, quantum can do on a scale we cant fully grasp. With quantum, were on the cusp of tackling colossal challenges and playing in the same computational league as Mother Nature herself. Quantum computing holds the potential to revolutionize drug development, craft materials that dont yet have names, and conduct endless simulations without the constraints of reality. Its poised to rewrite the rules of learning by doing, from engineering new proteins to offering a Black Mirror-esque glimpse into the world of online dating, says Katerina Syslova, from Tensor Ventures, a Czech deep tech-focused fund investing in AI, IoT, blockchain, biotech, and quantum computing across the CEE and UK

Central and Eastern Europe, a bedrock to exceptional tech talent, is no stranger to quantum technology research and development, through its academic institutions, participation in European projects, and a sprouting startup scene.

Zooming back to Europe, VC investment in quantum tech startups concentrates on four main areas, according to The European Deep Tech Report 2023: quantum computers and processors ($362M), quantum cryptography ($156M), quantum computing software ($98M), and quantum chemistry and AI for chemical/biotech.

While the realization of quantum computing hasnt unfolded as swiftly as many anticipated, its adoption is undeniably making steady progress. Beyond companies pushing the boundaries of bare-metal hardware innovation, theres a notable surge in the quantum software realm. This includes not only software designed for quantum computers but also quantum-inspired algorithms that deliver remarkable results when run on conventional infrastructure, we are told by Enis Hulli, General Partner at 500 Emerging Europe, a venture capital fund investing in the region.

To experiment with quantum technology and achieve a minimum viable product requires substantial budgets. With budgets primarily allocated to testing purposes, companies are also limited in their ability to grow and scale.

Nevertheless, as the technology matures and demonstrates its worth, unlocking additional capital and larger budgets will become more attainable, similar to the growth trajectory observed in the field of AI, Enis Hulli believes.

Central and Eastern Europe is experiencing a notable upswing in interest and activity in the field of quantum technologies, says Hulli, further pointing to the participation of academic institutions and research centers in countries like Poland and Hungary in quantum research. Such projects in turn contribute to the growth of quantum knowledge and expertise within the region.

Hungary, for instance, has established a National Quantum Technology Programme (HunQuTech) to connect the country to the developing European quantum internet. Hungary is also the sole country from the region participating in the OpenSuperQplus European project, through the Faculty of Natural Sciences and the Wigner Research Centre for Physics at the Budapest University of Technology and Economics. The project aims to develop a 1000-qubit quantum computer.

It shouldnt be a surprise given CEEs access to a robust talent pool in mathematics and computer science, whose skills and expertise can be harnessed to drive innovation and advancement in quantum technologies.

A quantum technology startup scene is also emerging. As of October 2023, we tracked 18 Central and Eastern European quantum technology startups. Poland, in particular, sits among the countries with the highest number of startups working on quantum technologies (6 counted in the mapping below), behind only Switzerland, Spain, Netherlands, France, Germany, and the UK.

CEE innovators excel in one particular arena identifying technology gaps and challenges and then crafting tailor-made solutions. This may as well be the opportunity that CEE startups are uniquely poised to seize, observes Katerina Syslova from Tensor Ventures, who has invested in three quantum startups thus far, including Poland-based BeIT.

For investors, tapping into the opportunities presented by one of the most complex technologies out there is nothing short of a challenge.

We were smart enough to know we werent smart enough. So we partnered up with Michal Krelina, one of the best quantum experts there is. He is our guide and Vergiliuls in the landscape of technical due diligence. In our portfolio, were constructing interconnected stacks, and quantum is no exception, adds Katerina Syslova from Tensor Ventures.

All that said, building a comprehensive quantum ecosystem demands time, collaboration, and substantial funding.

However, its important to acknowledge that while CEE is making strides in quantum research and talent development, challenges remain in terms of securing the necessary infrastructure and funding, as well as competing on a global scale with quantum powerhouses like the United States, Canada, and China. To position itself effectively in the global quantum ecosystem, CEE must continue to foster academic and research collaborations, attract investment, and strengthen its overall quantum infrastructure, says Hulli.

Location: Ljubljana, Slovenia

Founders: Marjan Beltram, Peter Jegli

About: The company is designing cold neutral atoms QCs with a completely new and patented approach to preparing qubit arrays.

Stage & Funding: N/A

Location: Krakow, Poland

Founders: Wojtek Burkot, Paulina Mazurek, Witek Jarnicki

About: BEIT is a quantum computing software R&D company developing novel quantum algorithms and their implementations with the aim of pushing the boundary of what is possible on quantum hardware.

Stage & Funding: Seed, $4.1M

Location: Riga, Latvia

Founders: Girts Kronbergs, Maris Kronbergs, Girts Valdis Kristovskis

About: Entangle offers quantum-secure encryption for connecting mission-critical infrastructure and industrial IoT over public mobile networks.

Stage & Funding: Bootstrapped

Location: Zvodno, Slovenia

Founders: Andraz Bole, Nejc Lesek

About: Lightmass Dynamics provides Quantum Neural Models based-solution for simulation and visualization. The company offers an application framework that can be integrated into any existing physics or rendering software for real-time physics simulation and visualization.

Stage & Funding: Seed, $120,000

Location: Warsaw, Poland

Founders: Janusz Lewiski, Sebastian Gawlowski

About: Nanoxo is a chemical company designing and manufacturing various functional materials, including quantum dots.

Stage & Funding: Seed, $253,000

Location: Tallinn, Estonia

Founders: Guillermo Vidal

About: OpenQbit stands for the development of hardware and software easy to use with quantum technology. They provide anyone with the tools necessary to create devices that use quantum technology, machine learning, and neural networks.

Stage & Funding: N/A

Location: Patras, Archaia, Greece

Founders: Vasilis Armaos, Paraskevas Deligiannis, and Dimitris Badounas

About: The startups intention is to simulate drugs, chemicals, materials, and other quantum systems by utilizing quantum computing hardware that already exists. The team at PiDust is made up of quantum computing experts, physicists, software developers, and chemists.

Stage & Funding: N/A

Location: Bankya, Bulgaria

Founders: Boris Grozdanoff, Zdravko Popov, Svetoslav Sotirov

About: QAISEC foresees a future where AI technology serves humanity and does not endanger it. They believe that where human-made crypto algorithms fail physics never does. They are using quantum encryption solutions for finance, industry, state, entertainment, healthcare, critical infrastructure, and communications.

Stage & Funding: N/A

Location: Wroclaw, Poland

Founders: Artur Podhorodecki

About: They develop blue-light emitting, heavy metal-free quantum dots for advanced technology markets, and quantum dot-based inks, for printable optoelectronics.

Stage & Funding: early VC, $5.8M

Location: Prague, Czech Republic

Founders: Michal Krelina

About: Quantum.Phi provides consulting, analytics, and research services in quantum technologies (including quantum computing and simulation, quantum network and communication, quantum imaging, and quantum measurement). It specializes in applications for the space, security, and defense industry.

Stage & Funding: N/A

Location: Warsaw, Poland

Founders: Piotr Migda, Ph.D., Klem Jankiewicz

About: The company develops a no-code integrated development environment (IDE) for quantum computers to design, debug, unit-test, and deploy quantum algorithms for business.

Stage & Funding: Seed, $260,000

Location: Athens, Greece

Founders: Dr. Aggelos Tiskas, Dr. Takis Psarogiannakopoulos

About: The companys High-Performance Quantum Simulator (HPQS) is designed to specialize in Variational Quantum Algorithms (VQAs) and Machine Learning (ML) tasks. This will enable the automation of high-level, abstract quantum circuit generation and optimize it for efficient resource usage.

Stage & Funding: N/A

Location: Miercurea-Ciuc, Romania

Founders: Laureniu Ni

About: Quarks Interactive is the startup that developed Quantum Odyssey, the first game where you can learn the concepts of quantum computing. The startup also works with big IT companies, such as IBM, to create software that can power these unique computers.

Stage & Funding: Seed, 230,000

Location: Tallinn, Estonia

Founders: Petar Korponai

About: Quantastica builds software tools and solutions for hybrid quantum-classical computing.

Stage & Funding: $220,000

Location: d, Poland

Founders: Tomasz Szczeniak, Michal Andrzejczak,

About: They are building a cryptography accelerator through which any electronic device can be protected against quantum computer attacks. They use post-quantum standards recommended by the National Institute of Standards and Technology (NIST) for secure end-to-end encryption. One of the main features of the solution is crypto agility, enabling a wide area of application.

Stage & Funding: Seed, 450,000

Location: Zagreb, Croatia

Founders: Hrvoje Kukina

About: A Quantum AI startup working on quantum-enhanced machine learning (mostly deep reinforcement learning).

Stage & Funding: N/A

Location: Kepno, Wielkopolskie, Poland

Founders: Arkadii Romanenko, Igor Lykvovyi, Leszek Sawicki, Ruslana Dovzhyk

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CEE Is Getting Ready for the Future with Quantum Technology: 25+ ... - The Recursive

About a decade ago, Rob Hovsapian bought a sailboat. He named it Vger.

For non-Trekkies, Vger was a probe sent into space by 20th century Earthlings in the first Star Trek movie. The probes task was to collect as much knowledge as possible. And it does. After amassing two centuries worth of data, the probe becomes a sentient being and changes its name from Voyager 6 to Vger.

Hovsapian, a mechanical engineer at the National Renewable Energy Laboratory (NREL), donated his sailboat to the sailing club at his alma mater, Florida State University. But he will not entirely lose Vgerat least not in spirit.

At NREL, he is building another massive, knowledge-gobbling machine, one that could help solve future crisesmaybe not Star-Trek-level Earth-ending crises, but close. How can we build a reliable clean energy grid, for example? Or make it easier to evacuate from natural disasters? Or protect banks from quantum hackers?

As a national lab, we need to be looking at the big picture, Hovsapian said, things that we can address five to 10 years down the road.

Like the Star Trek crew, Hovsapian is an explorer, but his final frontier is the future. And his spaceship (Vger light) is something called Advanced Research on Integrated Energy Systems, or ARIES for short. This sophisticated, one-of-a-kind research platform can emulate how our future technologies, including power plants, batteries, smart phones, electric vehicles, smart buildings, and more, would communicate (or fail to communicate) during an emergency.

Now, Hovsapian is adding new features to his spaceship. He is connecting NREL to other labsincluding national laboratories and academic institutionsto build a SuperLab and study how the country could respond to a massive, national-scale crisis. And he is adding quantum computers to the ARIES platform to quickly identify patterns and improve emergency response.

Its our duty to start identifying these challenges and developing solutions, Hovsapian said. We dont want to wait until a problem happens before figuring out how to solve it.

In NREL's latest Manufacturing Masterminds Q&A,Hovsapian shares why he stopped building fighter jets and army radios; what his kids think he builds now; and what kind of rare, national events the SuperLab might help solve.

How did you end up becoming an engineer?

I always wanted to be an engineer. From elementary school all the way to college, there was no doubt.

Wow. How were you so sure?

I just knew. I was taking things apart. I always took my toys apart because I wanted to know how they worked, right? I took the television and VCRs apart.

Im sure your parents were thrilled with that. Then, why pick mechanical engineering as opposed to a different engineering niche?

I started my career as an aerospace engineer and then eventually, since I didn't know exactly what I wanted to do, I got into mechanical engineering. It was more diverse, and controls was always my passion.

What does that mean, controls?

In robotics, controls refers to how you drive, say, your robotic arm to a specific location and, in real time, control its position and speed to manufacture a product.

Oh, cool! So, I know you went to the University of Alabama for your undergraduate studies. What did you do after that?

I read a book by Professor Krishna Karamcheti, who had written a lot of fluid mechanics books that I studied during my undergraduate years. When I saw he was a faculty member at Florida State University, I reached out, and he invited me to come and visit. I not only ended up admitted into the graduate school; he also gave me a job. But he made me promise to finish my doctorate and support other students. So, ever since then, I always have two or three doctoral students that I advise. Thats me keeping that promise.

Sounds like a pretty good deal. What job did he get you?

My first job was with General Dynamics, an aerospace and defense company. That was 1989. I worked on building a next-generation army radio, using robotics and manufacturing lines. After that, I went to work for the U.S. Air Forces F-22 stealth fighter jet program. I automated the production of F-22 fighter jets, using an automotive manufacturing line, which was more cost-effective. Then, while I completed my doctorate, I worked as a program manager and board member for the United States Department of the Navys Office of Naval Research where I managed a research program focused on developing all-electric ships.

Wow!

Yeah. My kids asked me, What are you building now? and I tell them I build PowerPoint presentations. From F-22 to army radios to all electrical ships to PowerPoints. Thats not true. I mean, I do a lot of PowerPoint presentations, but I was also part of the strategic planning that helped build the ARIES research platform.

Before we get to ARIES, how did you go from the U.S. Navy to NREL?

I was also a faculty member at Florida State University at that time. When I left my defense job and took my first job in academia, my salary dropped by 30%. Most people told me that Im crazy doing that. But I dont want to leave my career having built 400 F-22s or 10,000 army radios. I want to leave a legacy of something and make a difference in the community.

I spent two years supporting the U.S. Department of Energys Water Power Technologies Office, and then I went to Idaho National Laboratory for five years. When I heard NREL was building ARIES, that was my passion, so I dropped everything, and here I am.

Perfect transition. Now, lets talk about ARIES. What is it?

ARIES integrates software and hardware to help us understand how clean energy technologieslike renewable energy devices, batteries, electric vehicles, hydrogen, and buildingswill work together in a future carbon-free grid. Nobody has done this before. Nobody has paired hundreds of devices. And here, we are talking about thousands of devices at scale.

Thousands! And what problems are you trying to solve with ARIES?

Were trying to understand next-generation problems that we cant solve through traditional classical computing or modeling.

For example, do we have enough power for electrical vehicles in case of an emergency? Today, we know where the gas stations are. Im in Tallahassee, Florida, right now. If a hurricane comes in and theres an evacuation mandate, people know how they are going to evacuate. If all of us are using electric vehicles, how is that going to work?

So, when rare events happen, how do we mitigate them? That requires a bit more integration between technologies, including cell phones, electrical vehicles, satellites, emergency response systems, and building management systems.

I also heard, to address even bigger, national-scale challenges, youre building a SuperLab that might need to emulate communication between thousands of different devices, right?

The challenges that were facing as a nation are going to be much, much bigger than one or two labs can tackle. The SuperLab ties academic and national laboratories together, integrating not only people but also resources to answer those big questions. We already demonstrated connecting two laboratoriesPacific Northwest National Laboratory and Idaho National Laboratory. Our goal is to connect seven laboratories and 10,000 devices to address a large national event. Thats called SuperLab 2.0.

Have you decided which national event you might address?

No. But it has to be a significant, rare event, like a Hurricane Katrina, the Maui wildfires, or the 2021 Texas freeze.

Our objective is to create a real-world event and environment, using actual hardware and various grid assetslike automation controls, energy storage systems, batteries, and wind turbineswhich lets us explore how we can address those rare events.

Interesting. But this is the Manufacturing Masterminds series, so how does all this relate to manufacturing?

All these technologies are next-generation devices that were building today. We need to think about how to make cell phones that can talk to weather stations and broadcast communications. 5G is a good example. People outside the United States are developing better 5G technologies than we are. Thats a sign that our advanced manufacturing is not on par with what we need today.

Gotcha. Are there other ways the United States manufacturing industry could outpace competitors?

Everybodys talking about quantum computing. Now, were tying quantum computing to our real-time simulation work that were doing at ARIES (called quantum in the loop). Hopefully, this will make it easier and faster for researchers to adopt quantum computing to solve next-generation power and energy system challenges.

So, would the quantum computers allow you to run faster simulations?

It would allow us to identify patterns much, much faster.

So, lets say you look at the state of charge of electric vehicles during a hurricane. With quantum computing, you can quickly find potential bottlenecks. That way, you can issue more effective evacuation notices. You could direct people to different routes and tell some to wait for an hour or two or charge at home X number of times before they go, so you dont have people stranded on the way with a hurricane coming in.

What advice would you give to those who might want to follow in your footsteps and help solve these future crises?

Absolutely do not follow in my footsteps. Just look at the big picture and see what you can do differently. Its OK to be wrong, learn from mistakes, and do something better the next time.

Interested in building a clean energy future? Read other Q&As from NREL researchers in advanced manufacturing, and browse open positions to see what it is like to work at NREL.

See more here:
Q&A With Rob Hovsapian: The Engineer Who Solves Crises Before ... - NREL