QuEra Computing Inc.’s cover photo
QuEra Computing Inc.

QuEra Computing Inc.

Research Services

Boston, Massachusetts 22,173 followers

QuEra Computing is the leader in quantum computers based on neutral atoms. Use our 256-qubit machine on AWS Braket.

About us

Located in Boston, QuEra Computing is a maker of advanced neutral-atoms based quantum computers, pushing the boundaries of what is possible in the industry. Founded in 2018, the company is built on pioneering research recently conducted nearby at both Harvard University and MIT. QuEra is building the industry’s most scalable quantum computers to tackle useful but classically intractable problems for commercially relevant applications. Our signature 256-qubit machine, Aquila, the largest publicly-accessible machine in the world, is available now for general use over the Amazon Braket cloud. For more information, visit us at quera.com.

Industry
Research Services
Company size
51-200 employees
Headquarters
Boston, Massachusetts
Type
Privately Held
Founded
2018
Specialties
Quantum computing, Quantum algorithms, Neutral atoms, Quantum optimization, Quantum simulation, Quantum machine learning, and Quantum applications

Locations

Employees at QuEra Computing Inc.

Updates

  • QuEra Computing Inc. reposted this

    View profile for Shihan Sajeed

    Program Director, Q4Bio, Wellcome Leap, Co-Founder, Phantom Photonics

    Updates on Nottingham and their QE-DFT!

    View organization page for Q4Bio - Quantum for Bio

    798 followers

    As Q4Bio approaches the conclusion of Phase 2, we are excited to share the incredible progress made by our performers over the past 18 months. Here is Nottingham with their project ‘Quantum computing for covalent inhibitors in drug discovery’ The Nottingham-Phasecraft-QuEra collaboration is pioneering a quantum-enhanced approach to drug development, focusing on covalent inhibitors. Researchers at the University of Nottingham have identified these inhibitors as a potential treatment for myotonic dystrophy—a debilitating genetic disorder that leads to progressive muscle weakness and wasting. With an estimated 6,500 people affected in the UK alone, this research could have profound implications. In phase 1, they developed a quantum-enhanced atomistic modeling, integrating classical simulation, quantum software, and quantum hardware. This provides computational chemists with a practical tool for incorporating quantum computing into drug discovery. In phase 2, leveraging NVIDIA GPUs for quantum emulations, they have built up an unprecedented database which represents the largest collection of molecular classical, quantum Hamiltonian and circuits, and in many cases computed ground state properties from emulation. By using this to train transferable models, they have a scalable path to large, quantum-enhanced simulations of the full drug molecule interacting with a protein. The team is led by PI Jonathan Hirst and co-PIs Katherine Inzani (University of Nottingham), Ashley Montanaro (Phasecraft), and Tommaso Macrì (QuEra Computing Inc.) For more details, see: https://lnkd.in/gWpMQuwW https://lnkd.in/g599RJAb #QuantumComputing #QuantumforBio #QuantumChemistry #QuantumSimulation #WellcomeLeap #QuantumAlgorithms #PracticalQuantumAdvantage #Q4Bio #DensityFunctionalTheory #CovalentInhibitors #UniversityOfNottingham #Phasecraft #QuEra

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  • ⏳ 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!

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  • 🧑🔬 "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/ϵ, with the given error tolerance:  ϵ - 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.

  • How much value does quantum deliver today? 💭 The promise in quantum computing lies in its proven ability to solve specific problems with industrial and scientific value faster than classical alternatives. Hypothetically speaking the value of quantum is limitless. However, demonstrations of "quantum supremacy" showcase our current limited abilities to solve these problems. 💡 Our Chief Commercial Officer, Yuval Boger, helps evaluate a balance between the true promise and current value of quantum solutions in this article. He gives suggestions for practices that will aid in the journey towards maximizing quantum value. https://lnkd.in/gMuxNxjC ⁉️ Do you determine quantum value based on recent milestones or the mathematically proven capability of quantum computing? Share your opinion in the comments below.

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  • ⚛️ Day 4 at APS Global Physics Summit 🧑🔬 The quantum momentum continues! Join Pedro Sales, Majd Hamdan, and Katie Klymko this morning as they explore breakthroughs in quantum error correction, AMO physics, and experimental quantum simulation. 📍QEC Experiments Beyond Surface Code Memory: March 20th - A logical magic state distillation factory based on neutral atoms - Pedro Sales from 8:12 - 8:24 AM at 151 (Level 1) - https://lnkd.in/eYkZmWcP 📍 AMO Analogs of Physical Phenomena: March 20th - Observation of string breaking on a (2 + 1)D Rydberg quantum simulator - Majd Hamdan from 8:24 AM - 8:36 AM at 253A (Level 2) - https://lnkd.in/eZ3HgGzg 📍 Experimental Quantum Simulation: March 20th - Observation of anomalies in the statistics of Kibble-Zurek defects (with NERSC) - Katie Klymko from 9:48 - 10:00 AM - https://lnkd.in/e2NgufYH 👉 Tomorrow will be the final day of the event. Make sure to stop by booth #1103 if you're attending and haven't already!

  • Quantum Creators Con - Wrap-Up Webinar 🌟 Don’t miss these valuable insights into unique quantum education projects that may inspire the next quantum workforce and broaden awareness. Join us next week for an exciting webinar featuring participants from Quantum Creators Con in New York last month. They will present their projects from the event and cover the unique creative mediums used to make neutral-atom technologies more accessible and engaging. https://lnkd.in/givhirbQ 🎤 Meet the Presenters: • The Quantifiers (CCNY) – Rohma Khan, Shakibul Alam, Thanjila Thahsin • Et Al. (NYU) – Cheewon Choi • Möbius (NYU) – Ray Wang, Ege Tezcan

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  • 🇦🇺 Join QuEra and Quantum Brilliance at Quantum Industry Day in Sydney! QuEra and Quantum Brilliance are hosting Quantum Industry Day Australia. Join us to explore how quantum computing is being adopted today, its integration with high-performance computing (HPC), and Australia’s role in the global quantum ecosystem. Event Details: 🗓️ March 31st 2025 🗺️ NSW Parliament (6 Macquarie St, Sydney NSW 2000), Sydney, AU ✅ Free of Cost 👉 Secure a Spot https://lnkd.in/gtWyPXpk The event is being held in the historic Jubilee Room at NSW Parliament—a space originally built as an Edwardian-style library for the Parliament House. 💡 Among floor-to-ceiling bookshelves and beneath a stained-glass tribute to Queen Victoria, we’ll be showcasing today’s diverse quantum solutions, empowering organizations to turn cutting-edge innovation into practical advantage. Some of the Featured Speakers Include: - Jenny Bungur, Director of Operations and Partnerships: Infleqtion - Andrew Dzurak, CEO & Founder: Diraq - Cathy Foley, Former Chief Scientist: The Australian Government - Rita Gatt, National Lead Partner, Risk Advisory: Deloitte - Nate Gemelke, Co-Founder & Chief Technology Specialist: QuEra - Nicholas Harrigan, Quantum Computing: NVIDIA - Maria Kieferova, Research Scientist: Google - Ludwik Kranz, Head of Quantum Engineering: Silicon Quantum Computing - Mark Luo, CEO & Co-Founder: Quantum Brilliance - Tommaso Macrì, Executive Account Manager: QuEra - Celia Merzbacher, Executive Director: QED-C® - Biliana Rajevic, Strategy and Corporate Development Lead: Quantum Brilliance - Dilan Rajasingham, ANZ Financial Services: Amazon Web Services (AWS) - Jessica Richman, Director, Investment/Quantum Technologies Lead: Australian Trade and Investment Commission (Austrade) - Mark Stickells AM, Chief Executive Officer: Pawsey Supercomputing Research Centre - Andrea Tabacchini, PhD, VP Quantum Solutions: Quantum Brilliance - Felix Thomsen, Chief Executive Officer: Iceberg Quantum - Peter Turner, Chief Executive Officer: Sydney Quantum Academy #Quantum #QuantumComputing #QuantumTechnology #EmergingTech #Australia #Sydney #QuantumAustralia #TechAustralia #Leadership

  • 👨🔬 QuEra Co-Founder Mikhail Lukin will be on stage at NVIDIA #GTC Tomorrow! NVIDIA CEO Jensen Huang is hosting quantum industry leaders to explore today's state-of-the-art quantum supercomputing and what the future has in store for useful quantum computing. 🌟 Quantum Computing: Where We Are and Where We're Heading [S74495] • Tomorrow, March 20th • 10:00 AM - 12:00 PM PDT • San Jose Civic, CA https://lnkd.in/g4rGxMUQ 💻 Not planning on attending the event? Register for online access and watch the live session or a recording from home free of cost.

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  • We are excited to showcase a new collaboration with NVIDIA on decoding quantum errors using AI. This is described in a new technical blog post: https://lnkd.in/gMjQAJcb Quantum computing faces a formidable challenge in error correction. As qubit counts grow, so do errors that interfere with fragile quantum states. Addressing this issue is paramount to building scalable, fault-tolerant quantum machines. Why Error Decoding Matters Traditional quantum error-correction schemes rely on classical methods that must interpret complex data from the quantum system in real time. As we push toward larger, more intricate quantum circuits, this becomes even more demanding. That’s where AI steps in. Machine learning algorithms—optimized on powerful NVIDIA GPUs—can rapidly analyze error syndrome data, and decode them more efficiently than conventional methods. The MSD Experiment & Early Results A key highlight from the blog is the MSD (Magic State Distillation) experiment. The results showed that for a 3 MSD circuit, the NVIDIA decoder outperformed the high-performing but poorly scaling MLE (Maximum Likelihood Estimation) decoder. It hints that machine learning, combined with high-performance GPU infrastructure, could significantly improve decoding compared to conventional methods. This proof of concept paves the way for larger-scale testing and potential integration into next-generation quantum systems. Leveraging NVIDIA’s GPU Acceleration By pairing quantum systems with GPU-accelerated resources, there is a potential to simulate and decode errors on a scale that is out of reach with the current decoding approach such as MLE. This collaboration showcased how NVIDIA’s software stack, including tools like CUDA-Q, streamlines the simulation of large quantum systems. Early results hint at a performance boost in correcting errors, which can be a game-changer for moving from demonstrations to real-world applications. Pushing Toward Scalable Quantum Hardware AI-driven error decoding represents a critical piece of the puzzle for realizing robust quantum computations. Combined with neutral-atom architectures—designed for high qubit counts and flexible connectivity—this work underscores the synergy between high-performance computing and quantum research. As we continue refining these AI-based techniques, we get one step closer to systems capable of tackling complex problems in fields like materials science and drug discovery. Looking Ahead The partnership with NVIDIA highlights a promising direction: using AI to shoulder the classical heavy lifting required to make quantum computing feasible at scale. It signals a future where quantum processors, supported by HPC infrastructure, can handle more ambitious tasks with fewer errors. By combining machine learning, GPU acceleration, and quantum hardware, we hope to forge a more reliable and powerful quantum platform.

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