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December 31, 2024
2025 Expert Quantum Predictions — Quantum Computing
https://thequantuminsider.com/2024/12/31/2025-expert-quantum-predictions-quantum-computing/
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December 31, 2024
2025 Expert Quantum Predictions — Quantum Computing
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December 10, 2024
Algorithmiq Joins the QuEra Quantum Alliance to Accelerate Healthcare and Life Sciences Breakthroughs on Neutral-Atom Quantum Computers
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In the News
December 3, 2021
Realizing quantum spin liquid phase on an analog Hamiltonian Rydberg simulator
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November 17, 2021
This quantum computing startup says it’s ready to take on IBM and Google
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QuEra Computing emerges from stealth with $17M to launch quantum device
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QuEra offers new quantum advantage based on Harvard and MIT research
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This new startup has built a record-breaking 256-qubit quantum computer
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A new quantum computer startup from Harvard, MIT raises $17M
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December 10, 2024
Algorithmiq Joins the QuEra Quantum Alliance to Accelerate Healthcare and Life Sciences Breakthroughs on Neutral-Atom Quantum Computers
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All Three Projects Powered by QuEra Computing Contributions Move to Phase Two of Wellcome Leap's Quantum for Bio Challenge, Focused on Healthcare and Biology Applications
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November 19, 2024
QuEra Launches Full-Stack Quantum Algorithm Co-Design Program to Maximize Quantum Computing Potential
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October 25, 2024
Healey-Driscoll Administration Awards $5 Million to Establish the Nation’s First Quantum Computing Complex
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AIST and QuEra Sign Memorandum of Understanding to Strengthen Collaboration Toward Commercial Use of Quantum Computers
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QuEra Computing announces investment from key strategic partner to accelerate development of large-scale, fault-tolerant quantum computers
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High-Fidelity Control and Entanglement of Rydberg-Atom Qubits
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Trimer quantum spin liquid in a honeycomb array of Rydberg atoms
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Quantum optimization with arbitrary connectivity using Rydberg atom arrays
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Hardware-Efficient, Fault-Tolerant Quantum Computation with Rydberg Atoms
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Enhancing Generative Models via Quantum Correlations
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Computing solution space properties of combinatorial optimization problems via generic tensor networks
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