QuEra Computing Inc.

John Timmer makes a good point in his Ars Technica article. While the precise implementation of syndrome processing - FPGA, ASIC, GPU, or something else - is yet to be determined, a classical co-processor is a good friend of any QPU with error correction. Read the entire article; https://hubs.ly/Q02GtWzS0

In the RealClearDefense article "Quantum Computing Must Remain at Forefront of National Security Efforts," Gary Roughead, a retired Admiral and former Chief of Naval Operations, emphasizes the critical importance of quantum computing for national security. Roughead argues that quantum computing technology, with its potential to break current encryption standards and offer unprecedented computational power, presents both significant opportunities and threats. Roughead highlights the urgency for the United States to invest in and prioritize quantum computing to maintain a technological edge over adversaries like China, which has already made considerable advancements in this field. He underscores the potential risks quantum computers pose to cybersecurity, particularly through their ability to decrypt sensitive information that current encryption methods protect. To mitigate these threats, Roughead calls for accelerated development and implementation of post-quantum cryptography, which is resistant to quantum attacks. He also advocates for a proactive approach in transitioning to quantum-resistant encryption to safeguard military and civilian data against future quantum threats. https://hubs.ly/Q02GtC4S0

We're a week away from Deloitte's Quantum Globalization Summit TOKYO 2024 organized by our friends from Deloitte and Strangeworks. Join our Chief Commercial Officer Yuval Boger together with Simon Phillips of Oxford Quantum Circuits (OQC), @Elica Kyoseva of NVIDIA, Norihiro Suzuki of Hitachi, Shinji Kikuchi of Fujitsu, Masayuki Shirane of NEC Corporation, Yasuichiro Izumi of Toshiba as well as William Hurley and Matt Terabe for an exciting afternoon of quantum discussions. Register here: https://hubs.ly/Q02GtVZF0 - デロイト トーマツ グループ https://hubs.ly/Q02GtVZF0

Congratulations to Prof. Peter Shor of Massachusetts Institute of Technology for being named the recipient of the IEEE Information Theory Society's 2025 Claude E. Shannon Award for consistent and profound contributions to the field of information theory. Prof. Shor needs no introduction, and has made everlasting contributions to quantum computing via Shor's algorithm, his work on quantum error correction codes, and foundational concepts in quantum information theory. https://hubs.ly/Q02GtWJl0 (Photo credit: Christopher Harting, MIT News)

A fascinating article in Quanta Magazine explores the deep foundations of scientific inquiry, emphasizing the underlying principles that make scientific exploration feasible. Physicist Nigel Goldenfeld discusses the concept of reductionism, which posits that understanding the fundamental building blocks of matter enables us to explain the universe's complex phenomena. However, he argues that this approach is limited, especially in explaining higher-level phenomena like consciousness or biological systems. Goldenfeld introduces the idea of "emergence," where large-scale behaviors arise from simpler interactions at smaller scales. This concept is particularly relevant in quantum computing, where the collective behavior of qubits can produce outcomes that are not easily predictable from the properties of individual qubits alone. Emergence helps explain how quantum computers can solve certain problems more efficiently than classical computers, leveraging phenomena such as superposition and entanglement. In the context of quantum computing, the discussion highlights the importance of understanding how complex systems behave and interact at different scales. Quantum mechanics' principles, though rooted in simple mathematical equations, lead to emergent behaviors that provide quantum computers with their computational power, illustrating the interplay between fundamental physics and complex systems https://hubs.ly/Q02Fpwvz0

We are pleased to share a new paper "Large-scale quantum reservoir learning with an analog quantum computer" on arXiv at https://hubs.ly/Q02Gm4Vz0 In the paper, we develop a general-purpose, gradient-free, and scalable quantum reservoir learning algorithm that harnesses the quantum dynamics of QuEra's Aquila to process data. Quantum reservoir learning on Aquila achieves competitive performance across various categories of machine learning tasks, including binary and multi-class classification time-series prediction. The QuEra team successfully demonstrated quantum machine learning on up to 108 qubits, the largest quantum machine learning experiment to date (the previous successful QML record was 40 qubits). We further observed comparative quantum kernel advantage in learning tasks by constructing synthetic datasets based on the geometric differences between generated quantum and classical data kernels. This demonstrates the potential of utilizing classically intractable quantum correlations for effective machine learning. If you want to try out quantum reservoir learning, tutorial notebooks covering proof-of-concept simulations and experiments are available at https://hubs.ly/Q02Gm4j90. A recent webinar covering the major results of the work is also available at https://hubs.ly/Q02Gm4TB0. Don't hesitate to contact QuEra team with potential project ideas and problems of interest amenable to machine learning. The full paper is at: https://hubs.ly/Q02Gm4Vz0

This Moody's article https://lnkd.in/gz8VFqCQ discusses the growing interest in quantum computing within the financial industry, highlighting its potential to solve complex problems like derivatives pricing and portfolio optimization. It outlines various quantum computing modalities and the considerations for selecting hardware and software. Key players like QuEra Computing Inc. and IBM are mentioned, along with the pros and cons of digital and analog quantum models. The article emphasizes the importance of use cases and algorithms, and explores the availability and costs of quantum computing resources.

What are surface codes? "Ruby" from QuEra explains in this short video https://hubs.ly/Q02DQ5D_0

An interesting article in HPCwire covers work by Sandia National Laboratories has highlighted the superior memory efficiency of quantum computers in solving certain mathematical problems as compared to classical computers. The research underscores that quantum computers can handle complex mathematical tasks with significantly less memory usage, leading to faster and more efficient computations. The study, conducted by theoretical computer scientists at Sandia and Boston University demonstrates the potential of quantum computing to revolutionize fields that require intensive computational power and memory, such as cryptography and materials science. https://hubs.ly/Q02FpxNH0

It's always exciting to return to #Q2B. Many team members we will be in Tokyo in two weeks to underscore how much we care about the Asian quantum ecosystem and to engage with customers and partners. Our CCO Yuval Boger will be leading a panel on quantum computing and #HPC together with leaders from National Institute of Advanced Industrial Science and Technology (AIST), NVIDIA and Agnostiq Catch us at the event or schedule a time here: https://hubs.ly/Q02FmLCJ0