We speak to the eminent researcher who works on various aspects of quantum information and computing.
BY DEBDUTTA PAUL
Peter Zoller is a professor and scientific director at the Institute for Quantum Optics and Quantum Information (IQOQI), University of Innsbruck, Austria. He is a theoretical physicist renowned for his pioneering contributions to quantum optics and quantum information. Prof. Zoller is best known for his theoretical proposals for using trapped ions and ultracold atoms as quantum systems. He has earned several prestigious awards, including the Wolf Prize in Physics and the Max Planck Medal.
Prof. Peter Zoller (PZ) spoke to Debdutta Paul (DP) on his recent visit to ICTS-TIFR for the ‘A Hundred Years of Quantum Mechanics’ program.
The full text of the interview is reproduced below. The answers are lightly edited, and long paragraphs have been split for readability. The questions and initials are in bold.
DP: My first question is, what do you think is the status of the foundational questions in quantum mechanics?
PZ: Many foundational aspects of quantum mechanics are related to entanglement, such as the EPR paradox and Schrödinger’s cat, among others. Initially, these concepts were discussed as Gedankenexperiments (thought experiments), but the game-changer was transitioning them into the realm of experimental physics. Testing Bell inequalities to explore quantum correlations and entanglement over large distances is one example. Another is building and scaling quantum computers, which essentially involves creating Schrödinger’s cats of increasing size in the laboratory.
So far, the evidence consistently shows that quantum mechanics, as we currently understand it, holds true even as we test and apply it to increasingly macroscopic quantum phenomena. What were once puzzles in the foundations of quantum mechanics have become experimental realities in laboratories and have paved the way for novel applications and quantum technologies.
However, at some level, certain aspects of quantum mechanics remain puzzling. A key example is the measurement problem, where we assume a divide between the microscopic quantum world and the macroscopic classical world.
DP: And has there been any real progress along those lines recently?
PZ: You mean, in the sense of resolving this with experiments?
DP: Experiments to understand how to resolve those paradoxes, such as the measurement problem.
PZ: While we have gained a much deeper theoretical and technical understanding of measurements — for example, reading qubits on a quantum computer — the fundamental question has remained unchanged.
Quantum optics has made significant contributions in this area. In experiments pioneered by Haroche and Wineland, single quantum systems were prepared and observed continuously, yielding single measurement trajectories. On the theoretical side, continuous measurement theory has been developed to answer questions such as: given a photon count trajectory observed in a single run of a laser-driven atom experiment, what can we infer about the dynamical evolution of the atom? This foundational work underpins our understanding of qubit readout in quantum computers. On a technical level, we have achieved a profound understanding. However, I am less certain that this progress has brought us closer to solving the measurement problem itself.
DP: Right… you mentioned quantum computers. Will they be a functional reality soon?
PZ: We currently have small-scale quantum computers in our laboratories. However, they need to grow significantly to become truly useful and fulfill their potential. A major recent advancement has been achieving error correction at the breakeven point, bringing us closer to fault-tolerant quantum computing — as reported by the recent Google experiment. The big open challenge is scaling up, and certain platforms may prove more promising than others. It will undoubtedly be a very long journey, but I firmly believe that, in the end, there will be a fully functional quantum computer.
There’s an obvious analogy with artificial intelligence. The basic ideas behind AI were developed 30, 40, or even 50 years ago. At that time, the necessary hardware was unavailable, and it took a long time for the technology to catch up. But what eventually emerged has been amazing and has exceeded our expectations. My personal feeling is that quantum computing will follow a similar trajectory. We need to wait for the hardware to advance, but I am confident that it will happen.
DP: With the boundary between quantum many-body physics and quantum information science getting increasingly blurry, what are the most important questions that straddle the fields?
PZ: A significant part of modern many-body physics focuses on understanding entanglement, from the classification of phases in condensed matter physics to scrambling and thermalization in non-equilibrium dynamics. Naturally, as soon as you mention the word “entanglement,” you are essentially talking about quantum information. Quantum information has firmly established itself as the language for describing these phenomena.
We now have quantum simulators in our laboratories, enabling us to study such questions through synthetic quantum matter. Once you begin asking questions about entanglement, you are talking about quantum information.
In a broader context, achieving quantum advantage for a meaningful problem remains a central question driving the field. On the technical side, error correction in large-scale devices, such as hardware-aware error correction strategies to manage the substantial overhead, is a critical area of focus.
DP: The current noisy intermediate-scale quantum (NISQ) devices that we have are quite noisy, but what are the opportunities for discovering novel phenomena that they present that we don’t have with conventional solid-state experiments?
PZ: Condensed matter and solid-state physics focus on synthesising quantum materials and studying their properties. In contrast, quantum simulators, as Noisy Intermediate-Scale Quantum devices, enable us to create and study artificial or synthetic quantum matter, offering insights that are both beyond and complementary to traditional condensed matter experiments. Today, we have learned to build NISQ devices in laboratories as faithful experimental representations of complex many-body problems. These devices allow us to explore the properties of many-body systems, often surpassing the capabilities of classical computational simulations.
Entanglement is a central feature of all these studies. With quantum simulators, we are realising Feynman’s vision to build controlled quantum devices to “solve the quantum many-body problem,” accounting for large-scale entanglement.
DP: Besides the practical and engineering challenges, what are the fundamental physics challenges to building full-fledged fault-tolerant quantum computers? In other words, what kind of fundamental physics progress will accelerate the field?
PZ: There are different paradigms of quantum computing. The quantum logic network model is the most widely pursued approach in today’s experiments. In this framework, we use qubits as quantum memory, quantum gates acting on these qubits, and readout mechanisms, and we have well-established methods for error correction.
However, there are alternative approaches to quantum computing. One example is measurement-based quantum computing, which has been explored far less in experimental settings. This paradigm involves preparing a cluster state — a highly entangled initial state — and performing measurements on the system to represent a quantum computation. Ultimately, this approach is equivalent to the quantum logic network model. Certain quantum hardware, such as photonic systems, may be better suited to this paradigm. Another promising approach is topological quantum computing, which is one of the most elegant methods for error-tolerant quantum computing. However, its experimental development is still in its infancy. We are only at the beginning of exploring and implementing these alternative, potentially promising forms of quantum computation.
DP: What areas in science and industry do you see benefiting from all these investigations on quantum simulations and quantum computation?
PZ: The first obvious answer is that quantum computers will be useful in physics as quantum simulators, providing insights into new materials and phase diagrams. We can even reverse the question and ask: given a list of desired properties, can we use quantum simulators to design novel quantum materials? Through experiments with these quantum devices, we “learn” the relevant Hamiltonians, which can then be passed on to our chemistry colleagues in the hope that they can synthesise the corresponding real materials. This approach also extends to quantum chemistry and the design of new drugs. A large-scale quantum computer might also enable us to explore heuristic algorithms. Quantum optimization is one promising example in this area.
Finally, there are other applications, such as in quantum communication or in developing entangled quantum sensors that achieve precision beyond what is possible with uncorrelated particles.
DP: What are the questions that will shape the future of quantum mechanics in the following century?
PZ: Quantum computing explores quantum mechanics by building larger and larger quantum systems, pushing the boundaries between the microscopic and macroscopic realms. This approach is quite different from the traditional path of studying quantum physics by investigating smaller and smaller scales, as in high-energy physics.
An exciting intersection lies at the interface of gravity and quantum physics, which we can explore by building quantum computers and testing quantum mechanics at this new frontier. It is a win-win situation: either our quantum computers will scale and perform as expected, or we will uncover new physics waiting to be discovered.
DP: Thank you so much for your time, Prof. Zoller.
The author thanks Ananya Dasgupta, Spenta Wadia, and Sthitadhi Roy for inputs and suggestions.