Year 4 Projects
Atomically Precise, Hybrid Inorganic-Organic Quantum Systems
Elevator Pitch: We focus on a modular, chemical approach to qubit design. By synthesizing new hybrid structures that combine inorganic crystalline materials with organic molecules we produce systems that can be easily adapted to meet the demands of different quantum applications (e.g. computing, sensing, communication).
Project Motivation: The field of quantum information science (QIS) has grown substantially over the last decade as recent developments make quantum computing, communication, and sensing technologies more feasible. While there are many approaches to qubit design, no system has been developed without critical drawbacks, whether that be extreme operating conditions (mK temperatures, ultra-high vacuums), lack of scalability, or unavoidable inhomogeneity in the material. It is critical that as this research grows and translates to the commercial and government sector we continue to develop and explore new materials systems for QIS. Hybrid donor-acceptor complexes have shown promise as spin qubit pairs (Harvey, JACS 2021, 143, 38, Harvey, JACS 2020, 142, 31) and single photon emitters (Nano Lett. 2023, 23, 11548) but suffer from inhomogeneity in the inorganic nanocrystal. We propose transitioning to atomically precise nanoclusters as the inorganic component coupled to redox active organic molecules. The goal is to establish fundamental photophysical and spintronic properties in these systems and optimize their design for either long spin coherence lifetimes (computing) or single photon emission (communication).
PIs: Samantha Harvey (Indiana University - Bloomington)
Quantum-Classical Hybrid Approaches to High-Dimensional Sampling
Elevator Pitch: Many scientific and engineering applications need many feasible solutions, not just one optimum, to quantify uncertainty and risk. We will develop a quantum-classical hybrid sampler that uses NISQ hardware to propose structured, non-local moves and a classical Metropolis-Hastings (MH) correction to ensure exact sampling from the target distribution, improving efficiency and robustness relative to classical methods.
Project Motivation: Classical MCMC and Langevin samplers often mix slowly in rugged or constrained landscapes because they rely on local moves. Short-depth quantum circuits and short-time quantum dynamics can generate correlated global proposals and combining them with MH acceptance yields a practical, verifiable path to quantum advantage on near-term devices.
PIs: Ruizhe Zhang and Alex Pothen (Purdue University), Fan Chen (Indiana University - Bloomington)
Q-DART: A Quantum-Based Framework for Real-Time Data Tampering Detection
Elevator Pitch: Data tampering poses a serious threat to real-time, safety-critical systems that rely on continuous data streams. Building on our Year 3 work, which entails developing a framework for detecting adversarial NLP inputs to machine learning (ML) models, we propose to generalize this approach to detect data tampering in real time. Our approach is designed to operate directly on observed data streams.
Project Motivation: Modern cyber-physical and autonomous systems rely on continuous streams of sensor data to make safety-critical decisions. These systems are therefore vulnerable not only to traditional cyber-attacks, but also to data-level tampering that can occur in real time and evade tamper detection methods. Prior work has shown that model-aware attackers can inject false sensor measurements that remain statistically consistent with system models, making detection difficult. Additionally, anomaly detectors themselves can be targeted through adversarial manipulation, allowing attackers to evade detection via adaptive attacks. Using quantum-enriched features can directly solve these issues by describing features in a way that cannot be reverse-engineered classically. Moreover, quantum features can further amplify differences between clean and tampered samples, improving separability. Addressing this gap is critical for improving the resilience, trustworthiness, and security of autonomous platforms.
PIs: J. C. S. Santos (University of Notre Dame)
Deterministic Creation and Atomically Precise Characterization of Quantum Defects in hBN
Elevator Pitch: We propose to develop atomically precise protocols to create, engineer, and characterize quantum emitters and spin defects in hBN to enable quantum technologies such as single photon emission and quantum sensing with scalability. Our approach integrates experimentally establishing the structure-property relationships of existing defects with developing atomistic routes to realize new designer defects exhibiting telecom-frequencies photon emission and long spin coherence.
Project Motivation: Quantum defects in hBN have been successfully demonstrated as single-photon emitters, spin qubits, and quantum sensors. However, the controlled generation and atomic-scale understanding of these defects remain elusive. Current fabrication techniques lack the precision to control defect type, density, and uniformity, often resulting in stochastic distributions with undefined local environments. Defect characterization is largely restricted to macroscopic ensembles, obscuring their intrinsic atomic nature and high environmental sensitivity. Consequently, unambiguous determination of the defect structure is challenging, and the understanding of structure-property relationships remains heavily reliant on theory. Innovative approaches that integrate deterministic defect creation with advanced atomic-precision characterization are therefore critical to overcome these obstacles and advance quantum information science and technology.
PIs: Tiancong Zhu and Tongcang Li (Purdue University)
Qubits-based simulation of quantum criticality to enable Hamiltonian discovery in quantum materials
Elevator Pitch: Until true entangled quantum sensors are mainstream, all real-world data streams – even those appearing from quantum processes - will remain classical. By training AI models to identify the underlying physics producing the data streams, we will enable Hamiltonian discovery from materials systems, with the ultimate goal of quantum certification of general datastreams, including quantum communications.
Project Motivation: The project is motivated by our success using D-Wave, IBM and QuEra to simulate material-responsive Hamiltonians such as the triangular lattice clock and Shastry-Sutherland model (SSM) and 1D spin chains. We successfully observed the correct Ising magnetization plateaus (PRX-Q 2020) and Transverse field Ising model (TFIM) and XXZ (PRL 2026) phases, validated against DMRG. In CQT Year-1, using quantum quench in D-Wave (Nature Comm. 2024), we discovered a novel quantum coarsening behavior close to the 3D-XY critical point, later corroborated by Google and QuEra (Nature). Deduction of new phases and exotic quasiparticles from Hamiltonians with spin frustration is an outstanding problem in quantum material science, particluarly in 2D or 3D where DMRG and QMC fail. Essential steps are: (1) Symmetry classification; (2) Regime identification (quantum vs. classical); and (3) Parameter estimation. This project addresses step (2), by deducing the universality classes of these Hamiltonians, a near-term application for quantum hardware. These results can be directly tested using the new scanning NV-Center magnetometer (arriving in Birck Nano-Center in May) on quantum materials such as HoB4. Co-PI Banerjee has more than 8 years of experience using quantum computers and annealers for material Hamiltonians. Co-PI Carlson’s pioneering use of AI methods to identify criticality from spatially resolved datastreams (including scanning NV center) led to the discovery of universal critical structures across several different quantum materials.
PIs: Arnab Banerjee and Erica Carlson (Purdue University)
Designing Superconducting Metamaterials to Expand Single Photon Detection Capabilities
Elevator Pitch: We aim to design a new class of superconducting metamaterials based on serpentine coupled-quantum-wires inspired by theories of high temperature superconductivity. This will enable a new class of single-photon detectors with key advantages over existing designs including tunability across a range of photon wavelengths.
Project Motivation: Dynamic stripe theories of high-temperature superconductivity predict that superconductivity in these materials arises from interactions among emergent, fluctuating quantum wires in which transverse wire fluctuations enhance superconducting correlations. Our preliminary results using bosonization theory show that this phenomenon can be extended to metamaterials based on static, meandering quantum wires. The key result is that static geometries with incommensurate wavelengths destabilize all inter-wire interactions except Cooper-pair (Josephson) tunneling. This selective survival of Josephson coupling, in turn, dramatically enhances superconducting correlations across the device. Recent advances in nanowire arrays patterned on LaAlO3–SrTiO3 (LAO/STO) and LaAlO3–KTaO3 (LAO/KTO) interfaces, with highly tunable carrier density, geometry, and coupling, now allow experimental access to these regimes. Together, these developments motivate a novel single-photon detector design.
PIs: Erica Carlson and Jukka Vayrynen (Purdue University)
Decomposition-Based Approaches for Practical Quantum Optimization
Elevator Pitch: Our project develops quantum algorithms for discrete optimization by leveraging problem decomposition to address practical applications in engineering and science, including pharmaceutical process design, sensor placement in water networks, and network interdiction for defense and power system operations.
Project Motivation: Optimization involves science and engineering, advancing algorithms and hardware, including quantum techniques. Though solving combinatorial problems scales exponentially in the worst case, practical needs require efficient solutions. We use decomposition algorithms to harness quantum computing for real-world optimization.
PIs: David Bernal and Alex Pothen (Purdue University)