A new framework for building topological subsystem codes based on anticommuting quantum spin liquids has been developed by Vaibhav Sharma and Sumiran Pujari at Rice University, in collaboration with the Indian Institute of Technology Bombay. Sharma and colleagues demonstrate that these models, derived from modifications of the toric code, possess an extensive ground state degeneracy crucial for robust quantum error correction. Unlike conventional stabilizer codes which rely on commuting operators, the approach leverages an extensive set of anticommuting local conserved operators, resulting in a topological subsystem code with unique properties including a notable increase in undisturbed local gauge qubits. This construction offers a flexible template for designing new quantum error correcting codes adaptable to diverse quantum hardware platforms and geometries, addressing a critical need in the field of scalable quantum computation. Kagome lattice geometry enables threefold reduction in quantum error correction measurements A novel class of topological subsystem codes now requires threefold fewer measurements than existing designs, representing a significant advancement in reducing the overhead associated with quantum error correction. The implementation of these codes on a kagome lattice geometry necessitates only weight-3 local check operator measurements, a substantial reduction from the previously required weight-4 measurements common in many subsystem codes. This reduction in measurement complexity is achieved without compromising the ability to maintain an extensive number of undisturbed local gauge qubits, simultaneously enabling strong error correction capabilities. Built upon the principles of anticommuting quantum spin liquids, the framework provides a flexible template adaptable to diverse quantum hardware platforms and lattice geometries, potentially enhancing encoding rates or improving error thresholds for practical quantum computation. The kagome lattice, characterised by its corner-sharing triangles, provides a natural structure for implementing these low-weight check operators. For a square lattice of size L x L, the resulting code is an [L², 2, L] code,
Jul 16, 2026 · via quantumzeitgeist.com
Key takeaways - The performance of any quantum computer can be evaluated using three fundamental metrics: programmable qubits, qubit operations, and maximum circuits per second. - Programmable qubits measure scale by counting the qubits users can directly control and incorporate into quantum algorithms. - Qubit operations measure quality by indicating how many complex operations a quantum computer can reliably execute. - Maximum circuits per second measures speed by capturing circuit throughput, or how much useful computation a quantum system can perform over time. - Circuit throughput is a key indicator of quantum computing price-performance, helping quantify computational cost efficiency. - These metrics apply across quantum-computing modalities, including superconducting, trapped-ion, quantum-dot, and other hardware platforms. They give us a simple way of comparing quantum computers across different hardware modalities and platforms. IBM has long tracked the progression of quantum computing hardware performance across three fundamental dimensions: scale, quality, and speed. Together, they tell us not only what a quantum computer can do, but also how efficiently and cost-effectively it can do it. So, what are the specific metrics we use to quantify these dimensions? - Scale: Programmable qubits. How many qubits can you program directly? - Quality: Qubit operations. How many of the most complex operations can a system reliably execute? - Speed: Maximum circuits per second (circuit throughput). How much useful work can a system perform per second, and at what cost? These metrics provide a clear picture of the performance, computational capability, scalability, and cost efficiency of today’s quantum computers, regardless of the underlying hardware technology. They capture essential aspects of performance that apply across modalities—from IBM’s superconducting hardware to trapped-ion, quantum-dot, and other quantum computing approaches. Even as quantum computers grow more powerful and less error-prone, the underlying framework will remain largely the same, though some of the
Jul 16, 2026 · via ibm.com
Imagine this. You're catching up on some emails. Verifying your identity with a passport picture. Paying an invoice with your bank details. In the background, a "bad actor" is collecting all of your encrypted emails. For now, that data is just an indecipherable jumble of letters and numbers. But the person harvesting it is patient. They're waiting for something called "Q-Day" to arrive. That's the day a quantum computer will be powerful enough to uncover not only your online data, but classified documents and spy secrets. "Right now encryption is protecting this data," Sushmita Ruj, associate professor at the University of New South Wales' Institute for Cybersecurity, says. "But what if a computer comes in later that decrypts everything? It becomes a real catastrophe." And depending on who you ask, Q-Day is right around the corner. The algorithm that changed everything This digital doomsday situation was set in motion in 1994, when a computer scientist called Peter Shor came up with a radical idea. Professor Shor gave a talk at the famous Bell Labs in New Jersey on how a quantum computer could solve a maths problem much faster than a regular computer. Somewhere along the way, his talk got misinterpreted. People started to assume he had solved a much larger maths problem called factoring. When Professor Shor gave his talk, he hadn't. But by the time the rumour mill caught up with him a few days later, he had. It was a huge deal, but it takes some maths to understand... Factors are pairs of numbers that divide another number evenly without remainders. Take the number 77. Its factors are seven and 11. You could guess the factors of 77 even without using a calculator. But when the number gets big - potentially thousands of digits long - it
Jul 16, 2026 · via rnz.co.nz
PsiQuantum has announced Victor Peng as CEO, Rob Soderbery as executive vice president and Sriram Sitaraman as CIO, supporting the company’s efforts to scale its engineering, operational and commercial capabilities, and guide its next phase of growth. Peng’s move to CEO follows his own appointment on an interim basis in February. “PsiQuantum is entering an exciting new chapter,” said Peng. “Building the world’s first utility-scale quantum computers is one of the most ambitious engineering challenges ever undertaken, and the opportunities enabled by our silicon photonics platform extend well beyond quantum computing. Realizing that potential requires exceptional leadership, operational excellence, and the ability to build technologies, teams, and infrastructure at global scale. Rob and Sriram are outstanding leaders who will help accelerate our momentum as we build the company and platform that will shape the future of computing.” Soderbery brings over three decades of experience building and scaling top computing and infrastructure technologies to the company. In his new role, he will advance PsiQuantum’s silicon photonics platform, accelerating its application across AI networking and other next-generation computing infrastructure, the company said. He’ll also help scale engineering and operational capabilities needed to bring the technologies to market. “PsiQuantum has built one of the most compelling technology platforms I’ve seen in my career,” said Soderbery. “What impressed me just as much was the caliber of the team building it. The company’s silicon photonics platform creates a unique opportunity to deliver utility-scale quantum computing while opening new opportunities across advanced computing infrastructure. Just as exciting is the opportunity to help scale the company itself, bringing together world-class talent to build and deploy technologies that transform entire industries.” Before joining PsiQuantum, Soderbery was executive vice president and general manager of Flash Business at Western Digital, and before that, he led a multi-billion-dollar portfolio spanning enterprise
Jul 16, 2026 · via washingtonexec.com
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Jul 16, 2026 · via youtube.com
Last-mile and fleet routing plans start going stale the moment they're dispatched. Traffic shifts, weather turns, a new order comes in, a truck breaks down, and the route you just built is already behind before drivers pull out of the lot.
Join D-Wave and Signal Mine for a look at how quantum optimization may help logistics teams re-plan in real time, not hours.
In this 45-minute session, Jason Gautereaux (D-Wave) and Jim McBride (Signal Mine) will cover:
- Why fleet routing gets harder, not easier, as conditions change
- Why classical solvers trade speed for quality, and why that's a problem when disruptions hit
- Quantum annealing explores large solution spaces quickly, available today via cloud and hybrid solvers
- A live demo: a sample scenario re-optimizing after a disruption
A live Q&A follows. Bring your questions about production readiness, fleet size, and how to get started.
Jul 16, 2026 · via dwavequantum.com
The Center for Data Innovation recently spoke with Juha Riippi, CEO of Quanscient, a Finland-based startup developing an AI-powered engineering-simulation platform that combines cloud and quantum computing. Riippi explained how the company’s technology helps engineers simulate complex physical systems, explore more design options, and accelerate product development across industries ranging from semiconductors to aerospace. David Kertai: What does Quanscient offer? Juha Riippi: Engineering teams today face a fundamental bottleneck. They work with increasingly complex physical systems, yet many design tools still rely on computing power and software architectures that cannot efficiently handle today’s most demanding engineering problems. As a result, companies in semiconductors, energy, automotive, aerospace, and other advanced industries struggle to evaluate large design spaces, test many design options, and understand how different variables affect performance. This slows research and development, increases reliance on physical prototypes, and limits innovation. Quanscient addresses this challenge with a cloud-based engineering platform that allows engineers to design, simulate, and optimize complex systems before building physical prototypes. The platform combines multiphysics simulation—which models several physical processes, such as electricity, heat, mechanics, and fluid flow at the same time—with high-performance computing and machine learning. Engineers can run thousands of simulations in parallel, generate large physics-based datasets, and build AI models that predict performance much faster than running a full simulation every time. Kertai: How does your platform simulate complex physical systems? Juha Riippi: Engineers begin by creating a virtual model of the product or system they want to design. They import the geometry from computer-aided design software, assign material properties, and define operating conditions such as electrical currents, temperatures, mechanical forces, or fluid flow. The platform then solves the underlying physics equations to predict how the system will perform under real-world conditions. Instead of evaluating a single design, engineers can vary nearly every design parameter
Jul 16, 2026 · via datainnovation.org
Home to leading manufacturers, robotics pioneers, infrastructure builders and iconic gaming companies, of course, Japan is one of the world’s centers of AI — building across the full stack with NVIDIA technologies. This week NVIDIA and its partners in Japan are showcasing the AI ecosystem’s latest advancements. Check back here for updates. Wednesday, July 15, 4 p.m. PT 🔗 Japan’s Leaders Advance Healthcare and Life Sciences With NVIDIA Agentic and Physical AI Japan built the world’s most trusted names in medical technology and biopharma. Now the country’s healthcare leaders are engineering the next generational leap with AI, powered by NVIDIA. From autonomous surgical robots to AI-accelerated CT systems, and from agentic drug discovery platforms to virtual cell models, Japanese innovators are deploying NVIDIA technology to reshape medicine at every level. Agentic AI Accelerates Japanese Drug Discovery Japan’s pharmaceutical leaders are uniting around AI-powered drug discovery. Tokyo-1, the AI drug discovery consortium and platform operated by Xeureka, continues to expand, with Eisai joining this past April, bringing together leading pharma companies — Astellas, Daiichi Sankyo and Ono Pharmaceuticals — all advancing drug discovery using NVIDIA BioNeMo. Astellas has deployed nearly all BioNeMo NIM microservices within NVIDIA’s digital biology portfolio and is running BioNeMo Agent Toolkit, NVIDIA’s open platform that turns any AI agent into an autonomous life sciences scientist. It gives AI agents, software platforms and biopharma systems immediate access to NVIDIA’s full life sciences stack. Ono Pharmaceuticals is using the Boltz-2 NIM microservice to streamline and accelerate internal drug discovery. Daiichi Sankyo is conducting ultralarge-scale virtual screening on Tokyo-1 and leveraging NVIDIA RAPIDS to accelerate large-scale data processing. Xeureka is using NVIDIA BioNeMo to power its AI-driven drug discovery efforts, enabling researchers the flexibility to use the most appropriate models and tools across diverse discovery programs. SyntheticGestalt announced two products:
Jul 15, 2026 · via blogs.nvidia.com
Key Points - IonQ's stock has sold off heavily over the past two months. - The company's technology is what separates it from a crowded field of peers. IonQ(NYSE: IONQ) is one of the leaders in the effort to develop commercially viable quantum computers. While its stock has sold off recently, it could be only one major announcement away from skyrocketing again. After setting a 2026 high in late May, IonQ's stock has tumbled straight down, and is nearly 50% off its all-time high. While some investors may see that as a warning sign, I think it's a buying signal, as IonQ's stock price action often is driven more by broader market sentiment than its specific investment thesis. Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now, when you join Stock Advisor. See the stocks » Viable quantum computing is a fair way off IonQ is not a viable business right now. It has no profits and is only surviving on revenues from partnerships and the capital it raises through debt and share issuance. This makes it a highly risky stock, and when the market favors security over risk (as is the case right now), stocks like IonQ struggle. That's one of the primary reasons for its sell-off, as the company posted solid first-quarter results. During that quarter, IonQ delivered 755% year-over-year revenue growth. Some of that growth came via acquisitions, but a healthy chunk also came from organic business growth, thanks to a new system sale and growing partnerships. IonQ expects that its organic growth rate will remain above 100% for the year, which is a fantastic result for an early-stage company. The reason why IonQ is a popular investment option in the quantum computing
Jul 15, 2026 · via theglobeandmail.com
IonQ (IONQ 4.86%) is one of the leaders in the effort to develop commercially viable quantum computers. While its stock has sold off recently, it could be only one major announcement away from skyrocketing again. After setting a 2026 high in late May, IonQ's stock has tumbled straight down, and is nearly 50% off its all-time high. While some investors may see that as a warning sign, I think it's a buying signal, as IonQ's stock price action often is driven more by broader market sentiment than its specific investment thesis. Viable quantum computing is a fair way off IonQ is not a viable business right now. It has no profits and is only surviving on revenues from partnerships and the capital it raises through debt and share issuance. This makes it a highly risky stock, and when the market favors security over risk (as is the case right now), stocks like IonQ struggle. That's one of the primary reasons for its sell-off, as the company posted solid first-quarter results. During that quarter, IonQ delivered 755% year-over-year revenue growth. Some of that growth came via acquisitions, but a healthy chunk also came from organic business growth, thanks to a new system sale and growing partnerships. IonQ expects that its organic growth rate will remain above 100% for the year, which is a fantastic result for an early-stage company. NYSE: IONQ Key Data Points The reason why IonQ is a popular investment option in the quantum computing space is its unusual approach. Its machines are built around trapped-ion qubits, a technology that sacrifices speed for accuracy. IonQ holds the world record for 2-qubit gate fidelity, which is a commonly used metric for gauging computing accuracy. The primary issue standing between every quantum computer developer and a commercially viable technology is that
Jul 15, 2026 · via fool.com
Abstract A quantum computer requires the ability to store and manipulate information globally to protect against local noise. Topologically ordered phases1,2 offer two routes: encoding information in the ground-state subspace3 or in anyonic excitations1,4,5. The toric code1 exemplifies the first approach but does not intrinsically support a universal gate set. The latter—topological quantum computation—implements gates by braiding non-Abelian anyons6 around each other. However, the simplest non-Abelian generalizations of the toric code cannot achieve universality by braiding alone7,8,9. Here we demonstrate that anyon fusion, used as a computational primitive, renders these minimally non-Abelian topologically ordered states universal. We prepare a 54-qubit ground state of the quantum double of S3, the smallest non-Abelian group, on the H2 processor of Quantinuum. We encode logical information in the global fusion space of non-Abelian anyons, and by combining braiding with fusion, we realize a universal topological gate set and read-out, which we demonstrate by topologically preparing a magic state. This demonstrates that the S3 topologically ordered state is scalably preparable, yet rich enough to support a universal gate set. More broadly, this work opens up new pathways for harnessing the intrinsic properties of quantum matter to manipulate quantum information. This is a preview of subscription content, access via your institution Access options Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any time Subscribe to this journal Receive 52 print issues and online access $199.00 per year only $3.83 per issue Buy this article - Purchase on SpringerLink - Instant access to the full article PDF. USD 39.95 Prices may be subject to local taxes which are calculated during checkout Similar content being viewed by others Data availability The data generated in this study are available at Zenodo55 (https://doi.org/10.5281/zenodo.18054264) under open access. Code availability The
Jul 15, 2026 · via nature.com
Based on UC Santa Barbara professor John Martinis’s Nobel Prize–winning work in physics, Santa Barbara–based startup Qolab Inc. is developing new quantum technologies, making them more scalable and increasing the capabilities of quantum computing while reducing the cost. On July 2, Qolab announced that it raised $54.2 million in Series B financing and commitments led by UC Investments to support this work. The company was co-founded by Martinis, who won a Nobel Prize in 2025 for paving the way in superconducting quantum computing. He won the award alongside UCSB professor Michel H. Devoret. Admittedly, quantum computing is hard to dumb down. It is a type of computing based on quantum mechanics, which exploits quantum phenomena (things that happen on a quantum scale), to perform certain calculations significantly faster than normal computers. A regular computer solves problems using bits that are either zeros and ones. But quantum computing uses qubits, which can almost be a zero and a one at the same time — increasing efficiency. If a regular bit is like a coin on a table, meaning it can either be heads or tails, a qubit is more like a coin spinning in the air, almost allowing both probabilities to exist at the same time (not exactly, but this is a close-enough picture). It can be used for designing new medicines and materials, or breaking encryptions. This is what QoLab is doing. Martinis, Qolab’s chief technology officer, started the work that led to his Nobel Prize back in 1985. As previously reported by the Independent’s Ella Heydenfeldt, after joining UCSB in 2004, Martinis led the university’s Google Quantum AI partnership, where his lab built a 53-qubit processor that achieved “quantum supremacy” — solving a problem no conventional computer could handle. Qolab is advancing the same technology. “Quantum computing is entering
Jul 15, 2026 · via independent.com
Q-Day and the race to protect your data from quantum attack Thu 16 Jul 2026 at 5:00am Imagine this. You're catching up on some emails. Verifying your identity with a passport picture. Paying an invoice with your bank details. In the background, a "bad actor" is collecting all of your encrypted emails. For now, that data is just an indecipherable jumble of letters and numbers. But the person harvesting it is patient. They're waiting for something called "Q-Day" to arrive. That's the day a quantum computer will be powerful enough to uncover not only your online data, but classified documents and spy secrets. "Right now, encryption is protecting this data," Sushmita Ruj, associate professor at the University of New South Wales's Institute for Cybersecurity, says. "But what if a computer comes in later that decrypts everything? It becomes a real catastrophe." And depending on who you ask, Q-Day is right around the corner. The algorithm that changed everything This digital doomsday situation was set in motion in 1994 when a computer scientist called Peter Shor came up with a radical idea. At the famous Bell Labs in New Jersey, Professor Shor gave a talk on how a quantum computer could solve a maths problem much faster than a regular computer. Somewhere along the way, his talk was misinterpreted. People started to assume he had solved a much larger maths problem called factoring. When Professor Shor gave his talk, he hadn't. But by the time the rumour mill caught up with him a few days later, he had. It was a huge deal, but it takes some maths to understand. Factors are pairs of numbers that divide another number evenly without remainders. Take the number 77. Its factors are seven and 11. You could guess the factors of 77 even without
Jul 15, 2026 · via abc.net.au
Quantum computing is opening new possibilities for solving complex problems that are difficult for traditional computers to process. Through Amazon Braket, a cloud-based quantum computing service from Amazon Web Services, or AWS, researchers and students in the Sensor, Signal and Information Processing Center, or SenSIP, are gaining access to tools that support quantum computing research and education. Part of the Ira A. Fulton Schools of Engineering at Arizona State University, SenSIP recently hosted an Amazon Braket training and exposition event at the Artificial Intelligence Cloud Innovation Center at SkySong, the ASU Scottsdale Innovation Center. Amazon has donated nearly $78,000 in AWS credits to SenSIP to expand access to quantum computing and simulation tools. “The collaboration with Amazon is very important for us,” says Andreas Spanias, SenSIP director and a professor in the School of Electrical, Computer and Energy Engineering, part of the Fulton Schools at ASU. “Having Amazon involved with our center helps strengthen our research efforts and attract additional research support and industry consortium memberships.” The event brought together doctoral students, undergraduate researchers and faculty members to present projects that use quantum computing tools to address engineering and scientific challenges. “We have doctoral students who have been working in this area for a couple of years now, as well as students from across the country who are participating in the National Science Foundation Research Experience for Undergraduates,” Spanias says. The undergraduate research program gives students from universities across the country opportunities to conduct hands-on research, explore new pathways in STEM fields and build skills that support their future academic and professional goals. One example is work by Nandika Goyal, a Fulton Schools computer engineering doctoral student and researcher in SenSIP. Goyal used AWS credits to develop novel algorithms designed to aid cancer detection and classification. “She developed a quantum
Jul 15, 2026 · via news.asu.edu
QpiAI has released its Quantum SDK as open-source software, giving developers a pathway to run algorithms on the company’s 8-qubit and 25-qubit quantum computers via QpiAI-QCloud. The Python-based toolkit includes both local state-vector and density matrix simulators, allowing for algorithm prototyping and validation before utilizing actual quantum hardware. This move is designed to expand access to quantum software development for a global audience, from researchers and startups to enterprise innovation teams. “Quantum computing will scale only when developers can experiment, learn, and deploy without friction,” says Lakshya Priyadarshi, VP, Quantum Platforms & Solutions at QpiAI. QpiAI Quantum SDK Enables Algorithm Development and Hardware Access QpiAI has empowered developers with access to quantum computing resources through the open-source release of its Quantum SDK, providing a pathway to algorithm prototyping and direct hardware execution. The software, available at https://github.com/qpiai/quantum-sdk, represents a deliberate effort to democratize quantum software development, extending its reach beyond established research institutions to a global network of developers, startups, and enterprise innovation teams. QpiAI intends the SDK to serve as a foundation for building specialized quantum solutions across diverse fields including finance, logistics, materials science, and artificial intelligence. The Python-based SDK streamlines the development process with features designed for both novice and experienced quantum programmers. The SDK is engineered to support AI-assisted and agentic development workflows, enabling faster prototyping and implementation of quantum applications. QpiAI is actively targeting educational institutions, offering a ready-made foundation for quantum computing coursework, research projects, and developer training programs, with early adopters eligible for preferential commercial terms through the QpiAI Academic & Innovation Network. The release of the SDK is strategically aligned with India’s growing prominence in quantum technologies and its National Quantum Mission. “India is entering a defining decade for quantum technologies, and open-source software will be critical to building the talent, research,
Jul 15, 2026 · via quantumzeitgeist.com
Cybersecurity experts warn that about 10-20 years from now, quantum computers will have enough processing power to decipher common cryptography techniques like RSA and ECC, an event they call "Q-Day." These encryption protocols are the current gold standard in VPN tech, but when Q-Day arrives, they’ll no longer be enough. Post-quantum encryption (or PQE), which uses complex mathematical puzzles that even quantum computers struggle with, is your VPN provider’s answer to the Q-Day threat. But while Q-Day is still years away from actualization, PQE is a VPN feature you can enable today, to protect your data against hackers who might hold on to your encrypted data until quantum computers get strong enough to decrypt it. NordVPN, ExpressVPN, Mullvad, and others let you enable PQE right away with the click of a button. But is this future-proof encryption protocol necessary or worth the investment today? I’ll explain how it works, what it protects against, and which providers offer it so you can make up your own mind. How post-quantum encryption (PQE) works When you access the internet through a VPN tunnel, it basically scrambles your traffic data into unreadable code that can only be unlocked using a cipher key. That key is then securely transmitted to your device using a VPN handshake. So anyone who doesn’t have access to the encryption key, including your ISP, will not be able to interpret any useful information from your network and data usage. However, this technology only works because hackers don’t have access to hardware that can decrypt the scrambled network data without the encryption key. With quantum computing evolving as quickly as it is, security researchers estimate that it will be powerful enough to fully decipher your encrypted data without access to the actual key. Q-Day isn’t merely a distant threat. Attackers are
Jul 15, 2026 · via lifehacker.com
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Jul 15, 2026 · via youtube.com
IBM’s IBM-N said it had “faltered” in keeping pace with a shift in corporate spending from software to data-center infrastructure and would take a big earnings hit in the second quarter, in the clearest sign yet of AI’s growing toll on the sector. IBM’s shares tanked 25% on Tuesday, putting the stock on track for an even steeper single-day decline than it suffered during the 1987 “Black Monday” crash. Other software stocks also fell as investors fled the sector. That included Canadian stocks CGI Group, OpenText and Constellation software, all of which suffered losses of more than 4%. The warning shows that businesses racing to secure access to supply-constrained servers, chips and networking gear are diverting spending away from other technologies, adding to concerns about a software industry already rocked by the rise of AI tools that can write computer code and automate tasks. “In the last few weeks of June, we saw clients shift their quarterly capex spend toward servers, storage, and memory purchases to secure supply-constrained infrastructure ahead of expected price increases,” CEO Arvind Krishna said in a letter to investors. “While we anticipated some supply-chain related impact in our expectations, we did not anticipate the magnitude of the capex reprioritization,” Krishna said, adding that “numerous large deals” had failed to close as expected. IBM said the weakness was largely in its mainframe business, which sells high-powered computers and software that process millions of daily transactions for industries such as banking and airlines. It also noted that businesses were prioritizing cybersecurity spending given recent breakthroughs in AI hacking abilities. Anthropic’s advanced Mythos model has jolted businesses this year with its ability to expose flaws in existing software and encryption systems, pushing companies to ramp up cybersecurity. IBM said it expects revenue to rise just 1% to $17.2 billion
Jul 15, 2026 · via theglobeandmail.com
More than you might think, according to Professor Pawan Tyagi, director of the Center for Nanotechnology Research and Education (CNRE) at the University of the District of Columbia (UDC). Carotene, the molecule that gives carrots their bright orange color, is showing surprising promise in Tyagi's research into technologies that could underpin the next generation of computing, making it more powerful, energy efficient and sustainable. While advances in computing have largely meant making silicon-based electronics faster and more powerful over the years, Tyagi is investigating a different path, exploring a variety of materials that could one day complement or even replace conventional silicon-based devices in some computing applications. Recognized in 2025 by the World's Top 2% Scientists Network for his groundbreaking research, Tyagi is helping position UDC’s School of Engineering and Applied Sciences (SEAS) at the forefront of an emerging field known as molecular spintronics, where engineers, physicists and chemists are working together to answer one of computing's biggest questions: What comes after silicon? Opening the Door to New Computing Technologies Scientists have theorized for decades that individual molecules could someday serve as building blocks of electronic devices. The challenge wasn't imagining the possibility. It was figuring out how to connect molecules, some as small as one nanometer, into computing systems that could be manufactured practically and at scale. Tyagi believes his team has solved that problem. His patented Trenched Bottom Electrode Based Molecular Spintronics Device introduces a new way to integrate molecules into electronic hardware using conventional manufacturing techniques. Rather than limiting researchers to silicon alone, the approach creates a pathway for an almost limitless variety of molecules, each with unique electrical and magnetic properties. The innovation recently resulted in two U.S. patents and was presented in June at the prestigious Electronic Materials Conference. "One molecule could be DNA," Tyagi
Jul 14, 2026 · via udc.edu
Daniel Felipe Nino, Research Engagement Lead, Xanadu Introduction to Quantum Algorithms and Resource Estimation with PennyLane This workshop will give attendees a broad overview of how many quantum algorithms are built from a single recurring idea and how to account for the quantum resources needed to run these algorithms on real hardware. Through a series of hands-on exercises, attendees will learn about PennyLane functionalities for constructing and measuring core primitives such as the Hadamard test and quantum phase estimation, and for estimating the fault-tolerant resources an algorithm requires. By the end of the session, they will have hands-on experience building quantum programs with PennyLane and using its resource-estimation tools to assess gate counts, circuit depth, and hardware-dependent runtimes — connecting textbook algorithms to their practical cost. Xanadu is a Canadian quantum computing company with the mission to build quantum computers that are useful and available to people everywhere. Xanadu is one of the world's leading quantum hardware and software companies and also leads the development of PennyLane, an open-source software library for quantum computing and application development. This workshop is being organized for the USEQIP summer students but is open to all interested IQC members. Laptops are required to participate fully in the workshop; note that plugs are limited in QNC 0101. Pizza lunch will be provided. RSVPs are not mandatory, but appreciated for estimating order size and collecting any dietary restrictions: https://forms.gle/t7n334RWkfza1f7MA . Add event to calendar
Jul 14, 2026 · via uwaterloo.ca