Northwestern University researchers are leveraging NVIDIA technology to address the significant computational challenges in quantum research. Jens Koch, a theoretical physicist at Northwestern, and his team are focused on developing advanced simulations to model superconducting circuits used in quantum computing devices. As these simulations have become more complex, traditional computer processors have struggled to keep up with the necessary mathematical calculations.
To address this issue, Koch's group has started using NVIDIA graphics processing units (GPUs) and related software. GPUs are capable of performing thousands of calculations at once, making them well-suited for the demanding requirements of quantum simulations. Early testing has shown that NVIDIA GPUs can accelerate certain tasks by as much as 16 times compared to standard CPUs.
“NVIDIA has incredible expertise in GPUs, which make computations much faster,” Koch said. “With NVIDIA’s help, our algorithms will run much faster because they will use GPUs instead of regular computing processors. We have hit a major bottleneck for our simulations, so, for our work to continue to move forward, we are depending on this code.”
Koch is a professor at Northwestern’s Weinberg College of Arts and Sciences and serves as deputy director of Fermilab’s Superconducting Quantum Materials and Systems Center. He also co-directs the Northwestern-Fermilab Center for Applied Physics and Superconducting Technologies. Graduate students Danyang Chen and Lambert Lin are assisting with the new project.
The core element of Koch's research is the supercomputing qubit—a fundamental unit of information in quantum computers constructed from tiny electrical circuits. Qubits can exist in multiple states simultaneously, offering advantages over classical bits but presenting significant challenges in design and control.
“There is a shared challenge among researchers working in quantum computing,” Koch said. “That challenge is that quantum mechanics is fragile. As we make these systems larger, we have trouble controlling them. It’s hard to make quantum physics behave properly inside of a computer. We model these systems to help others understand how they behave and find the performance bottlenecks, so they can ultimately improve their performance.”
Koch's team previously developed an open-source software package called scQubits for modeling superconducting qubit systems; it has been downloaded over 340,000 times.
“It tries to simplify modeling for quantum devices,” Koch said. “Our package makes it as streamlined and as efficient as we can with current computers.”
The group is now integrating NVIDIA’s cuQuantum software development kit into scQubits to speed up two key mathematical calculations required by their models. Initial results indicate that using GPUs substantially increases processing speeds when tracking qubit interactions or calculating energy levels within large-scale circuits.
Although still early in testing GPU code within their simulations, Koch’s team anticipates releasing an updated version of scQubits featuring NVIDIA cuQuantum integration soon—potentially enabling faster runtimes and new simulation capabilities previously unattainable.
“Scientific computing is central to quantum research,” Koch said. “NVIDIA recognizes that and wants to help us make our software package run faster. We’re all very excited to see how these tools can boost the quantum physics research community.”