Quantum Computing

Quantum Starts Here

Rising above the noise: quantum-limited amplifiers empower the readout of IBM Quantum systems

A key pillar for deploying IBM Quantum systems into the cloud is the ability to read out their quantum states with high fidelity in real time. This critical capability is made possible using special kinds of low-noise microwave amplifiers, known as quantum-limited amplifiers.

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The Story Behind IBM’s 2019 Patent Leadership

IBM inventors were awarded 9,262 U.S. patents – topping, once again, the list for the most U.S. patents received, for the 27th year running. That brings the total number of IBM’s U.S. patents to over 140,000.

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IBM and Daimler use quantum computer to develop next-gen batteries

Electric vehicles have an Achilles Heel: the capacity and speed-of-charging of their batteries. A quantum computing breakthrough by researchers at IBM and Daimler AG could help tackle this challenge. We used a quantum computer to model the dipole moment of three lithium-containing molecules, which brings us one step closer the next-generation lithium sulfur (Li-S) batteries that would be more powerful, longer lasting and cheaper than today’s widely used lithium ion batteries.

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IBM Takes Its Quantum Computer to Japan to Launch Country-Wide Quantum Initiative

IBM quantum computing hardware comes to Japan – thanks to a new initiative between IBM and the University of Tokyo.

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Get to the heart of real quantum hardware

Our newest freely available quantum computing system takes one more step toward bringing the lab to the cloud. It features pulse-level control, and when coupled with today’s release of the new version of Qiskit (version 0.14), any IBM Quantum Experience user now has the ability to construct schedules of pulses and execute them. The role of experimental quantum physicist is now available to anyone with internet access.

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IBM Quantum Network Adds New Member, Stanford University’s Q-Farm Initiative

At the Q2B 2019 Conference, IBM announced that Stanford University’s Q-Farm initiative, a collaborative with the SLAC National Accelerator Laboratory, has joined the IBM Quantum Network. As a member organization, Q-FARM will collaborate with IBM to accelerate joint research in quantum computing and develop curricula to help prepare students for careers that will be influenced by this next era of computing across science and business.

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IBM and the Unitary Fund Unite for Open Source Projects for Quantum Computing

We are pleased to announce our support to grow the community of quantum enthusiasts and explorers, by partnering with the Unitary Fund to provide funding for grants and priority access to certain IBM Quantum systems.

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IBM and Wells Fargo Collaborate to Accelerate Innovation

IBM Research is embarking on a multi-year, collaborative effort with Wells Fargo focused on research and learning that is intended to enhance the company’s artificial intelligence and quantum computing capabilities. Together with IBM Research, Wells Fargo plans to accelerate its learnings to inform innovation initiatives that reimagine the future of financial services in a way that is designed to deliver customer experiences that are simple, fast, safe and convenient.

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Qiskit – Write once, target multiple architectures

Qiskit has the flexibility to target different underlying quantum hardware with minimal additions to its code base. To demonstrate this, we have recently added support in Qiskit for trapped ion-based quantum computing devices, and enabled access to the five-qubit trapped ion device at the University of Innsbruck, hosted by Alpine Quantum Technologies.

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Building single-atom qubits under a microscope

In the paper “Coherent spin manipulation of individual atoms on a surface,” published in the journal Science, our team demonstrated the use of single atoms as qubits for quantum information processing. This is the first time a single-atom qubit has been achieved using a Scanning Tunneling Microscope.

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On “Quantum Supremacy”

Regarding Google's "quantum supremacy" paper, we argue that an ideal simulation of the same task can be performed on a classical system in 2.5 days and with far greater fidelity. This is in fact a conservative, worst-case estimate, and we expect that with additional refinements the classical cost of the simulation can be further reduced.

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