QuEra Computing Inc.

"Quantum-computing-enhanced algorithm unveils potential KRAS inhibitors" ?? In this work, researchers used quantum computing to design molecules for targeting KRAS, one of the most difficult cancer-related proteins. They did this by utilizing hybrid quantum-classical machine learning techniques, and were able to find two compounds with promising biological activity. Read here: https://lnkd.in/gyb4hEVj ?? The team utilized the effects of superposition and entanglement to create a more accurate representation of distributions in complex data sets. ?? The resulting quantum data allows for classical machine learning algorithms to represent complex, high-dimensional probability distributions more efficiently than classical models. Researchers hypothesize that quantum prosperities help escape barren plateaus more effectively during optimization in machine learning, resulting in a more comprehensive exploration of solution space, potentially uncovering molecular structures classical models could not generate within the same time frame.

? Next Monday: Quantum Industry Day Australia! QuEra and Quantum Brilliance are proud to be hosting this event alongside industry moguls, technology providers, and government institutions. Join us and explore quantum computing, its path towards adoption, initiatives towards integration with high-performance computing (HPC), and Australia’s role in the global quantum ecosystem. Event Details: ? Next Monday, March 31st, 9:00 AM - 3:30 PM ?? NSW Parliament (6 Macquarie St, Sydney NSW 2000), Sydney ?? Free of Cost ?? Register Here https://lnkd.in/gtWyPXpk ?? ?????? ???????????? ?????????????? ?????????????? ??????????????: 9:30 - 9:45 AM ??????????????: The State of Quantum Computing in Australia: 9:45 - 10:15 AM ???????????????? ????????: Funding and Policy for Quantum Technologies: 10:15 - 10:45 AM ?????????? ????????????????????: Industry Adoption of Quantum Computing: 11:15 AM - 12:00 PM ?????????? ????????????????????: Building a Quantum Industry Ecosystem in Australia and Stimulating Adoption: 1:00 - 1:45 PM ????????: HPC & Quantum Integration - The Role of Supercomputing in Quantum Advancements: 1:45 - 2:10 PM ????????: APAC Quantum Technology Report: 2:10 - 2:25 PM ?????????? ????????????????????: Australia's Role in the Global Quantum Supply Chain: 2:25 - 3:10 PM ?????????????? ?????????????? & ???????????? ????????????????????: 3:10 - 3:20 PM In addition there will be breaks for coffee, food, and networking opportunities throughout the event. See the website above for the full program. Panels will be held by speakers from QuEra, Quantum Brilliance, the Australian Trade and Investment Commission (Austrade), Amazon Web Services (AWS), Deloitte, Diraq, Google, Iceberg Quantum, Infleqtion, NVIDIA, the Pawsey Supercomputing Research Centre, QED-C?, Q-CTRL, Silicon Quantum Computing, and the Sydney Quantum Academy.

?? Join us For a Special Forbes Tech Council Event: QuEra Computing: Unlocking the Power of Neutral-Atom Quantum Systems ?? April 22nd at 1:00 PM ET ?? Register at: https://lnkd.in/gbwUUHma Our Chief Commercial Officer will share how quantum computing is evolving from theory to practical deployment, how enterprises can prepare for this shift, and why the Quantum Processing Unit (QPU) could be the next GPU. Wondering how to prepare to leverage quantum computing as quantum transitions from theory to application? This webinar is for you.

?? Quantum Machine Learning for Small Data: Do More With Less ?? When data is scarce—whether in rare disease research, early-phase clinical trials, or drug discovery—traditional classical machine learning methods often struggle. Overfitting, poor generalization, and high variability make extracting insights a major challenge. ???? However, a new study by QuEra, Deloitte, Merck, and Amgen explores a compelling quantum-based alternative: Quantum Reservoir Computing (QRC). This approach leverages neutral-atom quantum hardware to handle nonlinear dynamics and enhance predictive accuracy—especially for datasets as small as 100–300 samples. In this blog we summarize our findings and address key factors in QRC. https://lnkd.in/gPVd5Eta arXiv Paper: https://lnkd.in/gPt6Dx-R

???? Quantum Australia Conference 2025 in Brisbane Began Today! This year's theme is "The Translation of Quantum" How current and future industries can leverage the power of quantum. Join us for discussions and presentations with world-leading quantum researchers, businesses, government decision-makers, startups, and big tech sharing the latest developments in quantum technologies. https://lnkd.in/g5tUxaYV ?? Nate Gemelke, QuEra Co-Founder and Chief Technology Strategist, and Tommaso Macrì, Executive Account Manager, are at the event. Are you attending and are interested in our neutral-atom technologies, advancements in error correction, or want to discuss the Australian quantum ecosystem? Schedule a Meeting: https://lnkd.in/gCPdrwVw

When QuEra isn't developing our leading neutral-atom technologies, we're skiing! ?? Members of our team journeyed outside the confines of Boston to Wachusett Mountain for our first company ski trip. They enjoyed a nice lunch at the base lodge and prime February snow conditions on a beautiful Friday morning. ?? At QuEra, we push the boundaries of what’s possible in quantum computing, but just like in physics, balance is key. We believe in working hard and playing hard, whether it’s tackling quantum challenges or shredding down the slopes. ?? Our team brings the same energy, precision, and camaraderie to our ski trip as we do to our research and engineering. Because breakthroughs happen when great minds come together—on and off the mountain. Interested in joining the team? We're hiring! https://lnkd.in/eCkTdDwz

?? Quantum Entanglement: no longer "spooky action at a distance"? Einstein once referred to quantum entanglement as "spooky action at a distance" but today it's a cornerstone of quantum computing. And thanks to new research, it just became easier to quantify. While previous studies explore the universal properties of quantum entanglement in magnetic, neutral, or superconductive materials, this work focuses on the local entanglement between one or two arbitrarily selected atoms. ?? Physicists at Osaka Metropolitan University developed simplified formulas to measure entanglement in strongly correlated electron systems. https://lnkd.in/eARBAWxj See the article and paper where the authors delve into formulas to calculate entanglement entropy and other key quantum informative quantities. ?? The work sheds new light on how quantum interactions behave at the nanoscale, opening doors to better control and application of entanglement in materials with diverse properties.

Updates on Nottingham and their QE-DFT!

? Final Day at APS Global Physics Summit ? As we wrap up an incredible week of discussions and discoveries, don’t miss Siva Darbha’s talk on collaborative research between QuEra, NERSC, and Berkeley Lab in detecting dynamical phase transitions. ?? Emerging Topics in Quantum Scars: March 21st - Dynamical quantum phase transitions in Rydberg atom arrays (with NERSC) - Siva Darbha from 9:48 - 10:00 AM - https://lnkd.in/e_M2dGkh ?? A huge thank you to all our incredible presenters and to the American Physical Society for organizing such an impactful event. It’s been an amazing week of quantum innovation!

???? "Ansatz-free Hamiltonian learning with Heisenberg-limited scaling" arXiv Link: https://lnkd.in/ePKz2KrH Quantum machine learning has diverse applications; one of which is the learning of the interactions that control the dynamics of a quantum system one wants to probe. This process is embodied by the idea of Hamiltonian learning, referring to the mathematical construct used to register and control those interactions. For a Hamiltonian with an unknown structure and unknown coefficients, it was an open question whether Hamiltonian learning is possible. ?? In this work, however, the authors propose an algorithm to achieve so with minimally reasonable conditions, showing that it is possible to process the learning tasks within a total running time being proportional to?1/?, with the given error tolerance: ?? - an optimal performance known as the Heisenberg-limited scaling. By using the?structure learning?and?coefficient learning?subroutine proposed in this paper the authors answer an important question, further connecting quantum computing and sensing applications.