Jay Gambetta’s Post

India has the second highest open access quantum computing users in the world after the US, at about 77,000, said Jay Gambetta, vice president of IBM Quantum. In an interview with The Economic Times last Friday, he said he saw immense opportunities for the Indian industry to become pioneers in quantum computing in high priority use cases such as “sustainability, energy, green hydrogen, efficiency of CO2 recapture process or nitrogen in agricultural yield & logistics, among others”. “There is algorithm discovery yet to be done in the scientific area to understand how to model different concepts using quantum computing. The next step would be to extend it to real world use cases,” Gambetta said. Quantum computing is a multidisciplinary field comprising aspects of computer science, physics & mathematics that utilise quantum mechanics to solve complex problems faster than on classical computers. Gambetta met faculty members from across India’s best universities at the IBM Research Bengaluru office on Thursday for special research & development collaborations. A day earlier, he met several industry leaders in Mumbai from sectors including manufacturing, energy, system integrators & research labs. Among those in attendance were a professor from Birla Institute of Technology and Science, Pilani, & an executive from Deloitte. Gambetta said he was excited to see India’s “impressive quantum growth story firsthand” during his first visit to the country and that IBM Quantum can further support India’s National Quantum Mission (NQM). However, he said that while India is among the top countries from an adoption perspective, Japan, South Korea & European countries are ahead in investing. “India has definitely got the adoption but not the business yet,” he told ET. In February, IBM announced that technology consulting company LTIMindtree had joined the IBM Quantum Network to explore quantum computing innovation for the benefit of its global clientele across multiple industries. Indian Institute of Technology, Madras also joined the network. “They have access to our premium systems, & all our 22 quantum computers that allow them to do algorithm discovery which can’t be done on classical computers,” he said. IBM & CDACINDIA Centre for Development of Advanced Computing (C-DAC) forged a collaboration in October last year to support the advancement of NQM by building competency in quantum computing technology, applications in areas of national interest & a skilled quantum workforce. Their activities focused on workforce enablement, development of industries and startups, research & development, & quantum services & infrastructure. The Union cabinet approved the NQM in April last year with an outlay of Rs 6,003.65 crore from 2023-24 to 2030-31. https://lnkd.in/gpjRi687 ETtech

India is uniqely Positioned to be a prime player in the quantum future

🚀 Exciting Times Ahead: IBM's Quantum Leap in Computing! 🌌 Hey LinkedIn fam! 👋 Did you know that IBM is at the forefront of a technological revolution that's set to redefine the boundaries of computing? 🌐✨ Join me on this journey as we explore IBM's groundbreaking advancements in Quantum Computing and the fascinating realm of Quantum Machine Learning. 🔍 Unraveling Quantum Computing: IBM has been leading the charge in the development of Quantum Computers. Unlike classical computers that use bits (0s and 1s), quantum computers leverage quantum bits or qubits. These qubits can exist in multiple states simultaneously, opening up a whole new dimension of computing power. IBM's Quantum Computers, available through the IBM Quantum Experience, allow users to access and experiment with quantum computing, pushing the boundaries of what's possible in computation. 💡 Quantum Machine Learning (QML): Enter the realm of Quantum Machine Learning, where classical machine learning meets the quantum world. IBM is making significant strides in the integration of quantum computing into machine learning algorithms. This promises to revolutionize industries by solving complex problems that are currently beyond the reach of classical computers. Imagine supercharging your machine learning models with the unparalleled capabilities of quantum computation! 🔬 IBM's Quantum Roadmap: IBM's Quantum Roadmap outlines a journey towards achieving Quantum Advantage — the point at which quantum computing surpasses classical computing for specific tasks. With an ambitious plan to build more powerful quantum systems and enhance quantum error correction, IBM is paving the way for a future where quantum computing becomes an integral part of solving real-world problems. 🌐 Join the Quantum Community: IBM is fostering a vibrant Quantum Community, encouraging collaboration and knowledge sharing. Whether you're a seasoned quantum physicist or a curious enthusiast, IBM's Quantum Community provides resources, tutorials, and opportunities to engage with quantum computing. 👩💻 Get Involved: Excited to dive into the quantum realm? IBM offers Quantum Experience for developers and researchers to experiment with quantum circuits, algorithms, and applications. Embrace the future of computing by getting hands-on with quantum technologies! 🚀 Conclusion: IBM's commitment to advancing quantum computing and quantum machine learning is shaping the landscape of the future. As we stand on the brink of a quantum revolution, let's celebrate IBM's strides in making quantum computing accessible and practical for the world. 🌟 Are you ready to ride the quantum wave with IBM? Share your thoughts and let's discuss the quantum future! 🌐💬 #ibm #quantumcomputing #quantummachinelearning #futuretech #innovation "

Last week, Rensselaer Polytechnic Institute (RPI) and IBM officially unveiled the world's first-ever IBM quantum computer on a university campus. Building on RPI's bicentennial celebration of 200 years of firsts, IBM Quantum System One will significantly enhance educational and research opportunities for the university, as well as with other academic institutions and organizations across the New York region that wish to partner with RPI. Faculty, researchers, students, and collaborators accessing the system will aim to advance quantum computing research, including the search for quantum algorithms that could lead to quantum advantage, while also actively building the next generation of the quantum workforce alongside IBM. "Standing at the forefront of quantum computing as the first university to host an IBM Quantum System One is a fitting celebration of RPI's pioneering legacy in our bicentennial year," said RPI President Marty A. Schmidt. "With trustee Curtis Priem's support and our enduring partnership with IBM, we'll utilize advanced computing for global problem-solving and train future quantum professionals, aiming to establish the Capital Region as a hub for quantum innovation – our own 'Quantum Valley'. The new IBM Quantum System One at RPI is powered by a 127-qubit IBM Quantum 'Eagle' processor, to offer RPI's network of researchers, students and partners dedicated access to a utility-scale quantum computer. In 2023, IBM demonstrated the ability of IBM Eagle to produce accurate calculations beyond classical, brute-force simulation methods. Known as #quantum #utility, this signaled the start of an era in which quantum systems can serve as scientific tools to explore problems in chemistry, physics, materials, and other fields in the search for quantum advantage: the point at which a quantum computer can solve a problem better than any known classical method. "It is fundamental that IBM works with our global ecosystem of partners, including world-renowned universities and research institutions such as RPI, to discover and map new algorithms to the most difficult challenges that quantum computers can solve. We will do this by fostering a quantum workforce of the future and ensuring that the next generation is equipped with the skills to use these systems to their fullest potential." - Dario Gil, IBM SVP and Director of Research. As the first university in the world to house an IBM Quantum System One on its campus, RPI has a unique opportunity to develop new quantum curriculum and educational programs aimed at upskilling the quantum workforce. As IBM and RPI build initiatives to prepare the future talent base of technology workers, the organizations expect their joint learnings to influence global workforce development and skills-building programs. #University #NewYork https://lnkd.in/gzY4MgBG

University of Southern California has a new agreement with IBM that boosts #quantum research by scientists and students and will reinforce the university’s status as a leader in quantum research and a top trainer of the nation’s tech workforce - writes Emily Gersema. “The new IBM Quantum Innovation Center at USC will be a pillar in our ability to do cutting-edge research in the area of quantum computing and to train future scientists who will be making exciting discoveries,” said Daniel Lidar, the director of the USC Center for Quantum Information Science and Technology who will also direct USC’s IBM Quantum Innovation Center. “We are excited to collaborate with USC, not only to help advance their research interests, but to prepare their students to join a rapidly growing quantum workforce,” said Jay Gambetta, IBM Fellow and vice president, IBM Quantum. “And with increasing industry interest, USC will play an important connector role as an IBM Quantum Innovation Center, providing a path for organizations to jointly develop algorithms and use cases for practical applications of quantum computing.” “The remarkable innovation that underpins quantum computing is the result of decades of knowledge exchange between industry leaders like IBM and academic researchers at universities like USC,” USC Dornsife College of Letters, Arts and Sciences Dean Amber D. Miller said. “Building on this long tradition of collaboration, we will work together to accelerate the quantum revolution and deepen our fundamental understanding of the world.” “The quantum realm is an exciting and intriguing next frontier in computing, communications and sensing. USC has anticipated this emergence and has been at its forefront for more than a decade with the assembly of a strong group of faculty who advanced academic quantum computing and communications both on campus and at our own Information Sciences Institute,” said Yannis Yortsos dean of USC Viterbi School of Engineering. “With the proliferation of artificial intelligence and machine learning problems, and the need to assemble training data for those areas, we are going to have to deal with larger and larger datasets,” said Mahta Moghaddam, vice dean of research for USC Viterbi and a Distinguished Professor of electrical and computer engineering. USC Dornsife and USC Viterbi leaders expect even more interest in quantum coursework and scholarship now that the university is an IBM Quantum Innovation Center. And they are ready for a new wave of students and research. https://lnkd.in/gtMmv_kC

Researchers show classical computers can keep up with, and surpass, their quantum counterparts. Forming the edge environment from the norm network of a tensor network state. One of the edges e is split and all other indices of the network are contracted over, reducing the cut network to a single matrix where a singular value decomposition can be performed. Quantum computing has been hailed as a technology that can outperform classical computing in both speed and memory usage, potentially opening the way to making predictions of physical phenomena not previously possible. Many see quantum computing's advent as marking a paradigm shift from classical, or conventional, computing. Conventional computers process information in the form of digital bits (0s and 1s), while quantum computers deploy quantum bits (qubits) to store quantum information in values between 0 and 1. Under certain conditions, this ability to process and store information in qubits can be used to design quantum algorithms that drastically outperform their classical counterparts. Notably, quantum's ability to store information in values between 0 and 1 makes it difficult for classical computers to perfectly emulate quantum ones. However, quantum computers are finicky and have a tendency to lose information. Moreover, even if information loss can be avoided, it is difficult to translate it into classical information—which is necessary to yield a useful computation. Classical computers suffer from neither of those two problems. Moreover, cleverly devised classical algorithms can further exploit the twin challenges of information loss and translation to mimic a quantum computer with far fewer resources than previously thought. The scientists' results show that classical computing can be reconfigured to perform faster and more accurate calculations than state-of-the-art quantum computers. This breakthrough was achieved with an algorithm that keeps only part of the information stored in the quantum state—and just enough to be able to accurately compute the final outcome. "This work shows that there are many potential routes to improving computations, encompassing both classical and quantum approaches," "Moreover, our work highlights how difficult it is to achieve quantum advantage with an error-prone quantum computer." In seeking ways to optimize classical computing, Sels and his colleagues at the Simons Foundation focused on a type of tensor network that faithfully represents the interactions between the qubits. Those types of networks have been notoriously hard to deal with, but recent advances in the field now allow these networks to be optimized with tools borrowed from statistical inference. The authors compare the work of the algorithm to the compression of an image into a JPEG file, which allows large images to be stored using less space by eliminating information with barely perceivable loss in the quality of the image. #quantum #matrix #algorithms #qubits #tensor

What is quantum computing? Quantum computing is a rapidly-emerging technology that harnesses the laws of quantum mechanics to solve problems too complex for classical computers. Today, IBM Quantum makes real quantum hardware a tool scientists only began to imagine three decades ago available to hundreds of thousands of developers. Our engineers deliver ever-more-powerful superconducting quantum processors at regular intervals, alongside crucial advances in software and quantum-classical orchestration. This work drives toward the quantum computing speed and capacity necessary to change the world. These machines are very different from the classical computers that have been around for more than half a century. Here's a primer on this transformative technology.Why do we need quantum computers? When scientists and engineers encounter difficult problems, they turn to supercomputers. These are very large classical computers, often with thousands of classical CPU and GPU cores capable of running very large calculations and advanced artificial intelligence. However, even supercomputers are binary code-based machines reliant on 20th-century transistor technology. They struggle to solve certain kinds of problems. If a supercomputer gets stumped, that's probably because the big classical machine was asked to solve a problem with a high degree of complexity. When classical computers fail, it's often due to complexity. Complex problems are problems with lots of variables interacting in complicated ways. Modeling the behavior of individual atoms in a molecule is a complex problem, because of all the different electrons interacting with one another. Identifying subtle patterns of fraud in financial transactions or new physics in a supercollider are also complex problems. There are some complex problems that we do not know how to solve with classical computers at any scale. Why quantum computers are faster Let's look a an example that shows how quantum computers can succeed where classical computers fail: A classical computer might be great at difficult tasks like sorting through a big database of molecules. But it will struggle to solve more complex problems, like simulating how those molecules behave. Today, for the most part, if scientists want to know how a molecule will behave they have to synthesize it and experiment with it in the real world. If they want to know how a slight tweak would impact its behavior, they usually need to synthesize the new version and run their experiment all over again. This is an expensive, time-consuming process that impedes progress in fields as diverse as medicine and semiconductor design. classical supercomputer might try to simulate molecular behavior with brute force, leveraging its many processors to explore every possible way every part of the molecule might behave. But as it moves past the simplest, most straightforward molecules available, the supercomputer stalls. #snsinstitutions #snsdesignthikers #designthinking

Quantum Error Mitigation: A Crucial Step Towards Fault-Tolerant Quantum Computing The journey towards fault-tolerant quantum computing is still underway, but quantum error mitigation (QEM) has emerged as a critical tool to bridge the gap between noisy near-term devices and the ultimate goal of error-free computation. QEM encompasses a variety of techniques aimed at reducing the impact of errors in quantum circuits, enabling the execution of more complex algorithms and achieving useful results even with imperfect hardware. These techniques range from hardware-specific optimizations to software algorithms that extract reliable information from noisy measurements. The benefits of QEM are manifold: 1. Extends the capabilities of near-term quantum devices, allowing them to tackle more challenging problems 2. Improves the accuracy and reliability of quantum algorithms 3. Accelerates the development of fault-tolerant quantum computing 4. Enables the implementation of quantum algorithms that were previously impractical due to noise As quantum hardware continues to improve, QEM techniques are becoming increasingly sophisticated and effective. In the near future, QEM is expected to play a pivotal role in enabling practical applications of quantum computing. Here's a glimpse into some of the key QEM techniques: 1. State Preparation and Measurement: Optimising state preparation and measurement protocols can significantly reduce errors in quantum circuits. 2. Error Correction Codes: Encoding quantum information in a redundant manner using error correction codes allows for the detection and correction of certain types of errors. 3. Noise Modelling and Characterisation: Accurately modelling and characterising the noise properties of quantum hardware is essential for developing effective QEM techniques. 4. Algorithmic Error Mitigation: Algorithm-specific techniques can be employed to extract reliable information from noisy measurements, even when fault-tolerant error correction is not yet feasible. 5. Hybrid Quantum-Classical Approaches: Combining quantum and classical computing techniques can enhance QEM capabilities by leveraging the strengths of both computational platforms. QEM is a dynamic and rapidly evolving field, with new techniques and applications emerging continuously. As quantum hardware advances and QEM techniques mature, we can expect to see significant progress towards the realisation of fault-tolerant quantum computing and the transformative potential it holds. IBM's article on QEM : https://lnkd.in/da84-PzH

Hey LinkedIn Community, I wanted to share some thoughts on one of the most exciting developments in the software engineering industry right now: Quantum Computing. Recently, we’ve seen remarkable advancements in this field that could revolutionize how we solve complex problems. What is Quantum Computing? Quantum computing leverages the principles of quantum mechanics to process information in ways classical computers cannot. While classical computers use bits as the smallest unit of data, quantum computers use quantum bits or qubits. Qubits can exist in multiple states simultaneously (superposition), allowing quantum computers to perform many calculations at once. Recent Breakthroughs 1. Google’s Quantum Supremacy: Google recently announced that its quantum computer, Sycamore, achieved quantum supremacy. This means it performed a calculation in 200 seconds that would take the world’s most powerful supercomputers thousands of years to complete. 2. IBM’s Quantum Roadmap: IBM has been making strides with their Quantum Roadmap, planning to build a 1,000-qubit quantum computer by 2023. They’ve also introduced Quantum Computing as a Service (QCaaS), making quantum resources accessible to developers and researchers globally. 3. Microsoft’s Azure Quantum: Microsoft has integrated quantum computing into its Azure platform, providing developers with tools to create quantum applications. Their Quantum Development Kit (QDK) and Q# programming language are great resources for anyone looking to get started in this field. Why It Matters Quantum computing has the potential to: - Revolutionize Cryptography: It could break traditional encryption methods but also lead to the development of unbreakable codes. -Optimize Complex Systems: From supply chain logistics to traffic flow management, quantum computing can optimize systems that are too complex for classical computers. - Advance Drug Discovery: Simulating molecular structures quickly and accurately, speeding up the development of new medicines. - Enhance Machine Learning: Improving algorithms and processing large datasets more efficiently. Getting Started If you’re interested in diving into quantum computing, here are a few steps you can take: - Learn the Basics: Familiarize yourself with quantum mechanics principles. - Explore Quantum Development Kits: IBM’s Qiskit and Microsoft’s QDK are excellent starting points. - Join Communities: Participate in forums and groups focused on quantum computing. Quantum computing is still in its infancy, but its potential is enormous. As software engineers, staying updated with such groundbreaking technologies is crucial. Let’s continue to learn and innovate together! Feel free to share your thoughts or any interesting resources on quantum computing. 🌟 #QuantumComputing #SoftwareEngineering #TechTrends #Innovation #FutureTech

New Advances Promise Secure Quantum Computing At Home: Scientists from Oxford University Physics have developed a breakthrough in cloud-based quantum computing that could allow it to be harnessed by millions of individuals and companies. The findings have been published in the journal Physical Review Letters. Phys.Org reports: In the new study, the researchers use an approach dubbed "blind quantum computing," which connects two totally separate quantum computing entities -- potentially an individual at home or in an office accessing a cloud server -- in a completely secure way. Importantly, their new methods could be scaled up to large quantum computations. "Using blind quantum computing, clients can access remote quantum computers to process confidential data with secret algorithms and even verify the results are correct, without revealing any useful information. Realizing this concept is a big step forward in both quantum computing and keeping our information safe online," said study lead Dr. Peter Drmota, of Oxford University Physics. The researchers created a system comprising a fiber network link between a quantum computing server and a simple device detecting photons, or particles of light, at an independent computer remotely accessing its cloud services. This allows so-called blind quantum computing over a network. Every computation incurs a correction that must be applied to all that follow and needs real-time information to comply with the algorithm. The researchers used a unique combination of quantum memory and photons to achieve this. The results could ultimately lead to commercial development of devices to plug into laptops, to safeguard data when people are using quantum cloud computing services. "We have shown for the first time that quantum computing in the cloud can be accessed in a scalable, practical way which will also give people complete security and privacy of data, plus the ability to verify its authenticity," said Professor David Lucas, who co-heads the Oxford University Physics research team and is lead scientist at the UK Quantum Computing and Simulation Hub, led from Oxford University Physics. Read more of this story at Slashdot.