Subhasish Mandal, an assistant professor in the WVU Eberly College of Arts and Sciences Department of Physics and Astronomy, has been awarded a Faculty Early Career Development Program award from the U.S. National Science Foundation. The CAREER award, widely regarded as the foundation’s most prestigious honor for early-career faculty, recognizes researchers who demonstrate the potential to serve as academic role models while integrating research and education. For Mandal, the support will fuel an ambitious computational program aimed at understanding how the inner workings of exotic materials give rise to stable quantum behavior — and at building the free software tools that could allow scientists everywhere to accelerate the search for the materials that future quantum technologies will demand.

The core challenge that Mandal’s project addresses lies in the fundamental difference between ordinary and quantum information. Classical computers process information in bits, which exist strictly as either a 0 or a 1. Quantum computers, by contrast, exploit quantum states that can exist in many configurations simultaneously, a property that allows certain calculations to be performed at speeds unreachable by any classical machine. But that same quantum superposition is exquisitely sensitive. Stray electromagnetic fields, thermal fluctuations, or even the tiniest atomic imperfections in the material hosting the quantum state can destroy it, a process known as decoherence. Most quantum devices today operate only inside carefully controlled laboratory environments, shielded at cryogenic temperatures and isolated from external noise. For quantum technology to become practical and scalable, researchers need materials that can maintain quantum behavior in far less forgiving conditions.

“One of the biggest challenges in quantum technology is finding materials that can maintain their quantum behavior outside carefully controlled laboratory environments,” Mandal explained. “To overcome that challenge, we need to understand both how electrons interact with one another and how they interact with the natural vibrations of atoms in a material. Together, these combined interactions can dramatically reshape a material’s quantum properties and, if properly controlled, may help us design better materials for future quantum technologies.”

That dual interaction — electrons with electrons, and electrons with atomic vibrations — sits at the heart of the project. In any solid material, atoms are never perfectly still. They vibrate around their equilibrium positions, producing quantized lattice vibrations known as phonons. When electrons moving through the crystal scatter off these phonons, the resulting electron-phonon coupling can profoundly alter the material’s electronic structure. In some circumstances it enables superconductivity, the remarkable phenomenon in which electrical current flows with zero resistance and no energy loss. In others, it degrades the coherence of quantum states and undermines the very properties a quantum device depends upon. Understanding and controlling these interactions, Mandal argues, may hold the key to engineering materials whose quantum behavior is not merely preserved but actively stabilized by their internal structure.

The materials at the center of the research are not simple bulk crystals. Mandal’s team will focus on specially engineered substances assembled by stacking different two-dimensional layers one atomic plane at a time — a technique that has become one of the most powerful strategies in modern materials science. The approach is often compared to combining ingredients in a recipe: individually, the constituent layers may be rather ordinary, but stacked together in precise sequences, they can produce quantum properties that neither material exhibits on its own. Twisted or stacked layers of graphene, transition-metal dichalcogenides, and other layered compounds have already revealed superconductivity, magnetism, and topological phenomena invisible in the parent materials. By computing how electrons and phonons behave in these engineered stacks, Mandal’s group hopes to establish design principles for combining layers in ways that produce robust, technologically useful quantum phases.

To carry out this work, the project will rely on advanced computational methods and large-scale simulations capable of capturing the intertwined dance of electrons and atomic vibrations. These first-principles calculations, grounded in quantum mechanics rather than empirical fitting, allow researchers to predict whether a candidate material will exhibit special properties such as superconductivity before it is synthesized. A second major thread of the research concerns topological quantum states — exotic electronic phases whose defining characteristics are protected by the global structure of the material’s quantum wavefunction rather than by local details. This built-in protection means topological states can resist certain types of disturbances that would destroy ordinary quantum states. Many physicists believe that marrying superconductivity with topological quantum states could yield the basic building blocks of fault-tolerant quantum computers, whose information would be encoded in ways intrinsically immune to many sources of error. Identifying real materials that combine both ingredients is one of the field’s most sought-after goals, and computational screening offers a way to narrow an effectively infinite search space down to the most promising candidates.

Beyond the science itself, a central aim of the project is to democratize access to the computational machinery of quantum materials discovery. Mandal will develop free, openly available software that other researchers can use to hunt for new quantum materials, lowering the technical and financial barriers that often restrict advanced simulations to well-funded laboratories. The practical payoff could be substantial. “Instead of making every quantum material possible in a laboratory to see which perform well, researchers could first use the software to run simulations to identify the most promising options,” Mandal said. “Then scientists could focus their laboratory experiments on materials most likely to have useful quantum properties.” In a field where synthesizing and characterizing a single new compound can take months and considerable resources, the ability to computationally pre-screen candidates promises to compress discovery timelines and redirect experimental effort toward the materials most likely to succeed.

The award also carries a substantial educational and workforce mission, reflecting the CAREER program’s emphasis on integrating research with teaching. Mandal will create accessible educational materials explaining quantum science and technology to broad audiences, organize immersive summer workshops at WVU, and provide hands-on research opportunities for high school, undergraduate, and graduate students. Participants will learn computational skills that are increasingly indispensable not only in academic research but also in advanced manufacturing, high-performance computing, and the rapidly expanding quantum industry. “As quantum technologies move from the laboratory toward real-world applications, there is a growing need for a workforce that understands both the science and the tools behind them,” Mandal said. “This project allows us to train students at multiple levels and help prepare them for careers in one of the fastest growing areas of science and technology.” The training component holds particular significance for West Virginia, where building a skilled technology workforce is viewed as central to the state’s future economic development. Maura McLaughlin, chair of the Department of Physics and Astronomy and Eberly Distinguished Professor of Physics and Astronomy, praised the project as work “at the cutting edge of an extraordinarily innovative field,” noting that it will open new opportunities for West Virginia students while helping build talent critical to the state’s growth.

Mandal joined the WVU Department of Physics and Astronomy in 2022, and the CAREER award arrives on the heels of a remarkable stretch of recognition. In December 2025, his work on quantum materials was highlighted by the journal Nature Communications, and earlier in 2026 he received the Cottrell Scholar Award from the Research Corporation for Science Advancement. His Computational Quantum Materials Group receives support from an array of agencies and foundations, including the U.S. Department of Energy, the National Science Foundation, the U.S. Department of Defense, and the Research Corporation for Science Advancement — a breadth of backing that reflects the strategic importance of quantum materials research across the federal science enterprise.

Looking further ahead, Mandal frames the project as a step toward a fundamentally predictive paradigm for materials discovery. “The long-term goal is to create a way to predict which materials could be useful for quantum technology before they are ever made in a laboratory,” he said. “If we can find materials or a combination of materials that naturally support quantum states, we can help to build the foundation for new quantum technologies that could benefit society for decades to come.” If that vision is realized, the quantum computers and sensors of the future may rest not on materials discovered by accident, but on substances designed atom by atom, their quantum properties calculated and guaranteed long before the first crystal is grown.

News Publication Date: 10-Sep-2026

Web References: Not provided

Keywords

quantum materials, NSF CAREER award, quantum computing, electron-phonon coupling, superconductivity, topological quantum states, computational materials design, atomically layered materials, West Virginia University, quantum decoherence, high-performance simulation, quantum workforce training

The quantum bit, or qubit, stands as the fundamental building block of quantum computers, analogous to classical bits but vastly more fragile and complex. Superconducting qubits, favored for their scalability and integration potential, suffer from energy dissipation caused by environmental interactions. Critically, the rate at which this energy is lost does not remain constant; it fluctuates unpredictably due to microscopic defects and noise present within the materials composing the processor. Until now, typical measurement protocols, which rely on extended averaging over long durations, have failed to capture these rapid, sometimes hundreds of times per second, fluctuations.

Traditional characterization routines for qubit relaxation times involve prolonged measurement sequences lasting minutes, effectively smoothing over the transient dynamics inherent to the qubit environment. This averaging obscures the true temporal behavior of the qubit’s performance and limits the ability of quantum engineers to implement effective error mitigation or real-time correction techniques. The inability to “catch” these fast fluctuations means that quantum processors have been calibrated on incomplete data, potentially jeopardizing accuracy and stability during computations.

By leveraging a real-time adaptive measurement approach, the research team, led by Dr. Fabrizio Berritta, has overturned this limitation. Utilizing a custom-built classical controller powered by a field-programmable gate array (FPGA), the system continuously monitors and updates its estimate of the qubit’s relaxation rate with unprecedented speed—on the order of milliseconds. This performance nearly matches the qubit’s intrinsic fluctuation timescale, enabling precise following of the fast-varying environment that impacts quantum coherence and fidelity.

A key innovation lies in running the inference algorithm directly on the FPGA hardware. Unlike conventional setups that shuttle data back and forth between qubits and a general-purpose computer, this integration drastically reduces latency, allowing Bayesian models of the qubit relaxation rate to update with each individual measurement. This closed-loop, adaptive protocol guides subsequent measurement timing dynamically, maximizing informational gain and enabling the detection of relaxation rate changes approximately one hundred times faster than previous methods.

Programming FPGAs for such sophisticated adaptive control is a nontrivial task given their complexity and low-level hardware description requirements. Yet, the team succeeded in crafting a highly efficient coding framework reminiscent of Python, a language widely accessible to physicists, through the Quantum Machines OPX1000 platform. This accessibility Democratizes advanced quantum measurement techniques, opening doors for other research groups worldwide to emulate or extend these methods.

The FPGA’s rapid processing and flexible architecture allow it to perform simultaneous qubit state readout, Bayesian updating, and control pulse timing adjustments with minimal overhead. When combined with state-of-the-art superconducting quantum hardware from Chalmers University, the setup achieves a remarkable synergy: the qubit and its classical controller co-evolve temporally, enabling near real-time calibration and feedback during quantum operations. This approach mitigates the impact of rapidly fluctuating defect states invisible to slower characterization methods.

Crucially, the newfound ability to detect such fast fluctuations has unveiled surprising details about the qubit environment. Fabrication defects and microscopic fluctuators, once thought to vary only over long timescales, can alter qubit relaxation properties within fractions of a second. This revelation challenges existing assumptions and calls for renewed efforts to understand and engineer materials and architectures at microscopic levels to stabilize quantum processors.

The impact of this research extends beyond fundamental physics. Quantum computing promises revolutionary advances in cryptography, materials science, and artificial intelligence. Yet the road to practical quantum advantage hinges on qubits that maintain coherence reliably and consistently. Real-time adaptive tracking and control, as demonstrated by this work, represent a critical step in moving from static, slow calibrations toward dynamic, error-resilient quantum systems.

Moreover, this study highlights the powerful role of interdisciplinarity—melding classical high-speed electronics, sophisticated statistical inference, and cutting-edge quantum devices. It underscores how commercially available classical processors can be repurposed and optimized for complex quantum control tasks, bridging the gap between theoretical quantum science and practical engineering implementations.

As Dr. Berritta notes, current quantum processors’ performance is often bottlenecked by poorly behaving qubits overshadowing the “good” ones. This adaptive monitoring technique rapidly identifies such problematic qubits and tracks them in real time, enabling focused remediation and potentially informing hardware redesign choices. In time, this could lead toward feedback-driven quantum processors whose overall system quality dynamically adapts to moment-to-moment environmental changes.

This research is the fruit of an international collaboration spanning the Niels Bohr Institute, Norwegian University of Science and Technology, Leiden University, and Chalmers University of Technology. The collective expertise has yielded a quantum measurement platform that redefines the temporal resolution of qubit characterization and opens new avenues for quantum processor calibration and error correction frameworks.

In the broader context of quantum technology development, this progress exemplifies how nuanced understanding of physical qubit environments paves the way for robust, scalable quantum architectures. The dynamic interplay between quantum states and classical control electronics is becoming more central to the roadmap of scalable, reliable quantum hardware.

In conclusion, the real-time adaptive tracking of superconducting qubit relaxation rates ushers in a new era of quantum hardware diagnostics and control. By harnessing the power of FPGA-based adaptive measurement, researchers have lifted a veil on previously undetectable fluctuations that challenge qubit performance. This advancement not only deepens scientific understanding of quantum decoherence but also accelerates practical progress toward fault-tolerant quantum computing, pushing the boundaries of what quantum machines can achieve.

Subject of Research: Real-time adaptive measurement and control of relaxation rate fluctuations in superconducting qubits.

Article Title: Real-Time Adaptive Tracking of Fluctuating Relaxation Rates in Superconducting Qubits

News Publication Date: 13-Feb-2026

Web References:
DOI: 10.1103/gk1b-stl3

Image Credits: Fabrizio Berritta

Keywords: quantum computing, superconducting qubits, FPGA, real-time measurement, relaxation rate fluctuations, Bayesian inference, adaptive control, quantum hardware, decoherence, quantum processor calibration, quantum error correction