Jad Halimeh works at the intersection of theory and application. The LMU quantum physicist connects the world of equations with technological developments in quantum computing, seeking to understand exotic quantum systems.
On the office wall, a whiteboard displays all manner of equations: long formulas with operators describing complex quantum systems. Interspersed among them are curves in coordinate systems comparing measurements with simulations. Ask Jad Halimeh what these constructs mean, and he begins to explain, drawing additional curves and speaking about phase diagrams or hadronization – invariably drawing his visitor into the depths of the world of quantum mechanics.
He glances up briefly and continues explaining. “We are trying to understand exotic quantum mechanical many-body phenomena,” says Halimeh, recently appointed professor of quantum physics at LMU and a member of the Munich cluster of excellence MCQST. What he is referring to are controlled, purpose-built systems that experimentally recreate complex many-body physics: He calls them synthetic quantum systems.
This is a thriving field in which theory and experiment increasingly work hand in hand and where physicists probe a world known for elusive phenomena such as quantum entanglement – a property by which particles remain connected across vast distances. No part of such a system can be described without taking the rest into account. Classical computers quickly reach their limits here.
We use quantum mechanics to build quantum simulators; these demonstrate exotic phenomena that are difficult to replicate on classical computers.
Halimeh is forging new paths, attempting to describe these phenomena with the help of quantum simulators. He distinguishes between two basic forms: analog and digital. Analog systems recreate the relevant physics directly in the laboratory – for example, through the carefully tuned interactions of ultracold atoms trapped in optical lattice cages made of laser light. Digital quantum simulators, on the other hand, work with quantum logic operations that can be flexibly combined to create algorithms.
Within this universe, Halimeh can be understood as a bridge-builder of sorts, connecting the world of theoretical equations with technological developments in quantum computing and quantum simulation. “Essentially, we use quantum mechanics to build quantum simulators; these demonstrate exotic phenomena that are difficult to replicate on classical computers.”
As a theoretical physicist, Halimeh begins by writing down the key equations on his iPad. If an idea seems promising, he dives deeper with his doctoral researchers. The resulting numerical models can then be tested experimentally – an opportunity that MCQST increasingly provides. It is a globally unique intersection of theory and experiments. “It's a reciprocal game: We develop theoretical models that challenge our experimental colleagues at MCQST,” says Halimeh. “Similarly, they come to us with new, elegant methods and ask: What can we investigate physically with this? What phenomena could we make visible? Without experimental physics, we would progress much more slowly. We learn a great deal from each other.”
The highly dynamic field of synthetic quantum systems thrives on the linking of differing disciplines. Halimeh's group specializes in the quantum simulation of lattice gauge theories. Put simply, space and time are no longer treated as continuous; instead, the behavior of particles such as quarks or gluons is described at points and along lines of a fine lattice. The gauge theories that underpin this approach are mathematically so complex that they generally cannot be solved directly. Lattices make them more manageable.
This is where Halimeh comes in: His team has already made important contributions in the quantum simulation of lattice gauge theories and is among the world's leading groups for systems in one and two spatial dimensions. Indeed, two recent quantum simulation experiments Halimeh’s group did with Quantinuum constitute the largest realization of lattice gauge theories in two spatial dimensions.
Temporal snapshots of the early universe
One specific physical question concerns hadronization – a key topic in the Standard Model of particle physics through which quarks and gluons form bound particles such as protons and neutrons. Hadronization played a central role as the early universe cooled and can today be investigated experimentally through high-energy heavy-ion collisions, which briefly create a quark-gluon plasma. In this process, the constituent quarks and gluons eventually bind and thermalize, and ultimately form the matter we know today. What remains unclear is why these processes occur on timescales far shorter than theoretically predicted.
The initial state of the Universe is likewise known, but how these quarks eventually come together and bind with one another, is not clear. We simply don't know the full picture. To find out, we would essentially need temporal snapshots, much like the individual frames of a film. The most promising path to achieving this requires a quantum simulator.
At particle accelerators like the LHC at CERN, this question is difficult to answer, since they primarily provide access to the final state. The initial state is likewise known, but “how these quarks eventually come together and bind with one another, is not clear. We simply don't know the full picture,” says Halimeh. “To find out, we would essentially need temporal snapshots, much like the individual frames of a film. The most promising path to achieving this requires a quantum simulator.”
For the real-time quantum dynamics of interest here, classical computers are often restricted to comparatively small system sizes and short evolution times. A quantum computer, however, could allow Halimeh's team to incorporate larger systems and build a bridge to observations at particle accelerators.
To do this, a Hamiltonian operator would need to be implemented in three spatial dimensions – a computational blueprint that describes all interactions and energetic processes. It contains parameters that specify, for example, how quickly particles “hop” between lattice sites, how strongly they interact locally, or how they interact with neighbors. Properties such as spin are also captured in this manner. These quantities can be modified with various values. “Ideally, the quantum computer should reproduce exactly the physics encoded in this model,” says Halimeh – namely, at various points in time.
A question of quantum advantage
Collaboration with major tech companies
The image shows Google’s Quantum AI Willow chip with superconducting qubits. The Halimeh group used this quantum processor to observe the dynamics of perturbation-free localization in a gauge theory in one and two spatial dimensions. Halimeh’s team is also working with the new IBM Nighthawk chip with superconducting qubits (not pictured) and is conducting scattering experiments on this quantum processor within the framework of ga
These are complex, time-consuming endeavors. Halimeh always keeps the broader picture in mind, looking for where bridges connect to other pressing questions in the field. “My second pillar is what's known as quantum advantage,” he says. For researchers, this involves defining areas in which quantum simulators outperform classical computers. An aspect like hadronization can offer starting points for systematically searching for model calculations in which such an advantage can be realized. “We find ourselves at a productive intersection of many-body quantum physics, quantum simulation, and numerical simulations on classical computers,” says Halimeh. “That is also why major tech companies are interested in our research: We provide test cases and applications for their most advanced digital processors, each with more than 100 qubits.”
Halimeh says that his team is currently comparing highly precise numerical simulations with results from quantum simulations conducted in collaboration with colleagues from organizations such as Google Quantum AI, IBM Quantum, and Quantinuum. When the model and the calculations match well, the models are made more complex. “We deliberately search for parameter ranges where even our best classical methods come up against their limits,” says Halimeh. “And then we ask: If the classical computer fails here, what can the quantum computer do?”
That is also why major tech companies are interested in our research: We provide test cases and applications for their most advanced digital processors, each with more than 100 qubits.
Halimeh covers these topics at a rapid pace, a reflection of how fast the field itself has developed. His own trajectory has felt equally dynamic ever since he took interest in physics at age 13, back then in Beirut, Lebanon. His parents used to get him books and CDs on relativity theory and astronomy. He went on to study electrical engineering and mathematics in the US, completed a master's degree at KIT, and came to LMU for his doctoral studies in physics.
After stints in South Africa, Dresden, Heidelberg, and Trento, he returned to LMU first as a postdoc with physicist Fabian Grusdt, and then built his own research group – supported, among other things, first by an Emmy Noether Research Group Grant, then a free-floating Max Planck Research Group Award (1 out of 4 winners from over 400 applicants) in 2023, and an ERC Starting Grant in 2024. He has been a professor at LMU since last year.
For me, intuition is the most important thing. I gather clues, build a bigger picture from them, and try to understand what is really happening. Only then do I look for the simplest possible mathematical description.
Jad Halimeh
“Intuition is the decisive tool”
His group has grown quickly: He currently supervises four postdocs, seven doctoral candidates, and eight Master’s students, with four more doctoral candidates joining towards the end of the year. Having a larger group allows him to pursue an ever-growing number of topics in parallel. The formulas on the wall reflect this diversity. Asked how he arrives at his ideas, he says after a brief pause: “I would describe myself as someone who thinks phenomenologically. For me, intuition is the most important thing. I gather clues, build a bigger picture from them, and try to understand what is really happening. Only then do I look for the simplest possible mathematical description. Some people are more guided by equations. For me, intuition is the decisive tool.”
At the mention of intuition, the eye is drawn to a black-and-white photograph of Einstein hanging at the top of the whiteboard. “Albert Einstein is a great inspiration to me,” says Halimeh. “Not only because of his scientific achievements and creativity, but also because of his life's journey – the difficulties he had to overcome, the persecution he faced during the Nazi era, his independent thinking. He is a great role model for me.” A fitting inspiration for the times we live in – Einstein, too, was a bridge-builder in his own way.