physics

John M. Martinis

John M. Martinis is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand John M. Martinis rather than just read about it. In short: John Matthew Martinis (born 1958) is an American physicist and Professor of Physics at the University of California, Santa Barbara. He led a team to develop a superconducting quantum computer at the Quantum AI Lab.

Key takeaways

John M. Martinis belongs to physics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect John M. Martinis to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of John M. Martinis from memory before moving on to harder problems.

Reference excerpt

John Matthew Martinis (born 1958) is an American physicist and Professor of Physics at the University of California, Santa Barbara. He led a team to develop a superconducting quantum computer at the Quantum AI Lab. With the Sycamore processor, the team claimed the first evidence of quantum supremacy in 2019. He shared the 2025 Nobel Prize in Physics with John Clarke and Michel Devoret for joint work on macroscopic quantum phenomena in superconductors.

Early life and education John Matthew Martinis was born in 1958 and raised in San Pedro, Los Angeles. His father, a Croat from Komiža on the island of Vis near Split, Croatia, immigrated to the United States from Yugoslavia to escape the communist regime. His mother was born in San Pedro to parents who had also emigrated from Croatia. Martinis attended the University of California, Berkeley, where he received a B.S. in Physics in 1980, and a Ph.D. in Physics in 1987.

During his doctoral studies, Martinis investigated the quantum behaviour of a macroscopic variable, the phase difference across a Josephson tunnel junction. His doctoral advisor was John Clarke. During this time, he collaborated with Michel Devoret, a postdoctoral researcher at the time.In 1985, Clarke, Devoret, and Martinis presented their analysis of microwave pulses that demonstrated the quantized energy levels of a Josephson junction. This work would later become the basis for superconducting quantum computing.

Career Martinis joined the CEA Paris-Saclay in France for a first postdoc, and then the Electromagnetic Technology division at the National Institute of Standards and Technology (NIST) in Boulder, where he worked on superconducting quantum interference device (SQUIDs) amplifiers. Since 2004, Martinis has served on the faculty of the University of California, Santa Barbara. He held the title of Susan and Bruce Worster Chair in Experimental Physics for many years. The quantum device he developed in collaboration with UCSB colleagues was named Science magazine's 2010 Breakthrough of the Year. Google Quantum AI Lab, a partnership between UC Santa Barbara and Google, announced in 2014 that it had hired Martinis and his team in a multimillion dollar deal to build a quantum computer using superconducting qubits. He and his team published a paper in Nature in 2019, where they presented how they achieved quantum supremacy for the first time using the Sycamore processor, a 53-qubit quantum processor. Martinis resigned from Google in April 2020 after being reassigned to an advisory role. In 2020, Martinis joined Silicon Quantum Computing, a start-up founded in Australia by Professor Michelle Simmons. In 2026, he was appointed to the President's Council of Advisors on Science and Technology (PCAST) by President Donald Trump.

Qolab In 2022, together with CEO Alan Ho, he founded Qolab, a quantum computing private company based on semiconductor chip manufacturing. Since 2025, Qolab and Hewlett Packard Enterprise (HPE) are co-leading a consortium for the DARPA Quantum Benchmarking Initiative (QBI). The team is tasked with building an industrially useful quantum supercomputer by 2033. Within this partnership, Martinis and Qolab lead the hardware build, designing and fabricating the core superconducting quantum processors. In December 2025, Qolab launched Qolab Start, a superconducting qubit platform for hardware research and workforce development. Built for universities, research labs, and workforce training, it eliminates the need to build custom labs by providing pre-packaged hardware and direct access to quantum processors. Researchers can access these systems via an on-premise installation or through the cloud. In February 2026, Singapore's National Quantum Federated Foundry (NQFF) and Qolab formed a research collaboration to build integrated cryogenic low-pass filters (LPFs) for quantum processors. Martinis is the co-leader of Quantum Scaling Alliance (QSA), a global group that develops quantum computing technology and include Qolab as well as others such as Applied Materials, HPE, Synopsys.

Honors and awards In 2014, he shared the Fritz London Memorial Prize with Michel Devoret and Robert J. Schoelkopf. Martinis was chosen for Nature's 10, a list of people who mattered for science in 2019. In 2021, he received the John Stewart Bell Prize for Research on Fundamental Issues in Quantum Mechanics and Their Applications. In 2025, he received the Nobel Prize in Physics alongside his doctoral advisor John Clarke and Michel Devoret for the discovery of macroscopic quantum mechanical tunnelling and energy quantisation in an electric circuit. In 2026, he was decorated with the Grand Order of King Dmitar Zvonimir by the Croatian president Zoran Milanović for exceptional contribution to the development and promotion of quantum physics and technology on a global level, proud emphasis and preservation of Croatian origin, and special merit in transferring cutting-edge scientific knowledge to the Croatian academic community.

References

External links John M. Martinis on Nobelprize.org Interview of John Martinis by David Zierler on May 4, 2021, Niels Bohr Library & Archives, American Institute of Physics

Illustrations

Worked examples

Example 1 — a first encounter with John M. Martinis

Start with the simplest possible case. Write down what John M. Martinis claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to John M. Martinis before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about John M. Martinis ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of John M. Martinis

In research: John M. Martinis appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses John M. Martinis in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: John M. Martinis is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1958 births, 20th-century American physicists, 21st-century American physicists, so understanding it makes those chapters shorter.
In everyday life: Look for John M. Martinis outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “John M. Martinis” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study John M. Martinis in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what John M. Martinis means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain John M. Martinis out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is John M. Martinis in simple terms?

Why does John M. Martinis matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study John M. Martinis?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on John M. Martinis.