About

Kevin Smith is an Assistant Professor of Pediatrics at the University of Chicago, affiliated with the Department of Pediatrics and Comer Children's Hospital. His professional focus is within the field of pediatrics, and he is involved in research activities as indicated by his profile on the Research Network. He provides clinical services at Comer Children's Hospital located at 5721 S. Maryland Ave., Chicago, IL. Further details about his research interests, background, and key contributions are not provided in the available page text.

Research topics

• Computer Science
• Artificial Intelligence
• Physics
• Medicine
• Engineering
• Quantum mechanics
• Computer engineering
• Biology
• Genetics
• Database
• Mathematics
• Computational biology
• Mechanical engineering
• Computational science
• Algorithm
• Electronic engineering
• Psychiatry
• Telecommunications
• Bioinformatics
• Theoretical computer science

Selected publications

• Extrapolating Pauli Checks for Expectation Value Estimation on Noisy Quantum Devices

  IEEE Transactions on Quantum Engineering · 2026-01-01

  articleOpen access

  Pauli Check Sandwiching (PCS) is an error detection scheme that protects quantum circuits by inserting pairs of parity checks and discarding runs that signal errors. However, each additional check introduces noise and exponentially increases sampling costs. To address these limitations, we propose Pauli Check Extrapolation (PCE), an error mitigation technique that obtains measured expectation values from circuits with different numbers of checks and, analogous to ZNE, extrapolates to the “maximum check” limit - the theoretical number of checks required for unit fidelity. We test linear and exponential ansatzes, deriving the exponential form from the Markovian error model. Benchmarking PCE against ZNE on random Clifford circuits with simulated depolarizing noise shows PCE outperforming ZNE for larger circuits. On real IBM hardware, PCE achieves an accuracy of up to 99.2% (56.2% improvement over baseline), compared to ZNE's 82% accuracy (29.1% improvement over baseline), for 4-qubit circuits. To demonstrate a practical use case, we then apply PCE towards mitigating errors in classical shadow measurements. Our results show that PCE can achieve fidelities greater than the state-of-the-art Robust Shadow estimation, while significantly reducing the number of required samples by eliminating the need for a calibration procedure. We validate these findings on both fully connected topologies and simulated IBM hardware backends.

  PublisherDOI

• Computer Science Challenges in Quantum Computing: Early Fault-Tolerance and Beyond

  ArXiv.org · 2026-01-28

  articleOpen access

  Quantum computing is entering a period in which progress will be shaped as much by advances in computer science as by improvements in hardware. The central thesis of this report is that early fault-tolerant quantum computing shifts many of the primary bottlenecks from device physics alone to computer-science-driven system design, integration, and evaluation. While large-scale, fully fault-tolerant quantum computers remain a long-term objective, near- and medium-term systems will support early fault-tolerant computation with small numbers of logical qubits and tight constraints on error rates, connectivity, latency, and classical control. How effectively such systems can be used will depend on advances across algorithms, error correction, software, and architecture. This report identifies key research challenges for computer scientists and organizes them around these four areas, each centered on a fundamental question.

  PublisherOA PDF

• Quantum Noise Suppression at Scale with Crosstalk-Robust Gate Sets

  ArXiv.org · 2026-03-16

  articleOpen access

  We introduce crosstalk-robust gate sets, which are obtained using a novel, scalable optimal control problem exploiting locality. Through the suppression of pairwise quantum crosstalk, the gate sets enable robustness that extends to multi-qubit circuits. The IBM Quantum Platform devices provide a testbed for our gate sets, where we study their efficacy via error suppression protocols and randomized parallel single-qubit circuits of up to eight qubits. Furthermore, we provide the first known assessment of the impact of complete optimal control gate sets on quantum algorithms. Using a Hamiltonian simulation of a four-qubit transverse field Ising model, we show that noise-informed gates enhance median algorithmic performance by a factor of four over baseline Gaussian gates using the same calibration procedures. Lastly, we provide numerical evidence that optimized gate sets enable larger qubit-qubit coupling strengths that can cut two-qubit gate times in half. This result confirms that hardware-software co-design using quantum optimal control can create new opportunities for quantum computing architectures.

  PublisherOA PDF

• Computer Science Challenges in Quantum Computing: Early Fault-Tolerance and Beyond

  Open MIND · 2026-01-28

  preprint

  Quantum computing is entering a period in which progress will be shaped as much by advances in computer science as by improvements in hardware. The central thesis of this report is that early fault-tolerant quantum computing shifts many of the primary bottlenecks from device physics alone to computer-science-driven system design, integration, and evaluation. While large-scale, fully fault-tolerant quantum computers remain a long-term objective, near- and medium-term systems will support early fault-tolerant computation with small numbers of logical qubits and tight constraints on error rates, connectivity, latency, and classical control. How effectively such systems can be used will depend on advances across algorithms, error correction, software, and architecture. This report identifies key research challenges for computer scientists and organizes them around these four areas, each centered on a fundamental question.

  DOI

• Toward Human-Quantum Computer Interaction: Interface Techniques for Usable Quantum Computing

  2025-04-24 · 2 citations

  preprintOpen accessSenior author

  By leveraging quantum-mechanical properties like superposition, entanglement, and interference, quantum computing (QC) offers promising solutions for problems that classical computing has not been able to solve efficiently, such as drug discovery, cryptography, and physical simulation. Unfortunately, adopting QC remains difficult for potential users like QC beginners and application-specific domain experts, due to limited theoretical and practical knowledge, the lack of integrated interface-wise support, and poor documentation. For example, to use quantum computers, one has to convert conceptual logic into low-level codes, analyze quantum program results, and share programs and results. To support the wider adoption of QC, we, as designers and QC experts, propose interaction techniques for QC through design iterations. These techniques include writing quantum codes conceptually, comparing initial quantum programs with optimized programs, sharing quantum program results, and exploring quantum machines. We demonstrate the feasibility and utility of these techniques via use cases with high-fidelity prototypes.

  PublisherDOI

• Editorial: Realizing quantum utility: grand challenges of secure & trustworthy quantum computing

  Frontiers in Computer Science · 2025-09-29

  editorialOpen access

  INTRODUCTION In the unpredictable and inherently uncertain domain of quantum mechanics, the pursuit of pathways to comprehend this novel field is essential. Quantum computers present an innovative and accelerated methodology for computation; however, this advancement is not devoid of associated costs. Emerging challenges involving dependability, reproducibility, resilience, security, and privacy underscore the imperative to construct reliable systems that can deliver quantum advantages to researchers and the industrial sectors. From the investigation of quantum hardware, revealing untrustworthy and unreliable components, to Hamiltonian simulation within hybrid quantum and high-performance computing platforms, along with quantum cloud solutions and the engineering of dependable classical-quantum computing systems, the Research Topic Grand Challenges of Secure & Trustworthy Quantum Computing provides an exhaustive exploration of the reliability and trustworthiness of quantum computing technologies. The rest of this editorial is organized as follows. Sections 2 to 5 briefly summarize the articles in the Research Topic, while Section 6 gives an overview of the convergent themes arising from these studies. Eventually, Section 7 concludes the editorial. TRUST IN THE AGE OF UNTRUSTED QUANTUM HARDWARE The integration of quantum computing resources into cloud-based platforms introduces new risks attributable to potentially unreliable hardware vendors. Upadhyay and Ghosh (2024) propose a threat model where third-party providers could intentionally or inadvertently alter computation results. Such manipulations might change the probability distributions of observed states, leading to undetectable, suboptimal outputs, particularly hazardous for optimization in crucial infrastructure or sensitive security areas. The recommended mitigation approach is tailored to quantum limitations and involves distributing computation among multiple backends, mixing trusted and untrusted ones, to minimize the effect of compromised devices. Empirical results show improvements of up to 190× for quantum workloads, demonstrating that architectural redundancy, a cornerstone of classical fault tolerance, can be adapted to quantum clouds without excessive resource demands. 3 QUANTUM TRUSTED EXECUTION ENVIRONMENTS (QTEES) Although distribution strategies help detect and mitigate faulty output, they do not protect the confidentiality of quantum programs. Trochatos et al. (2025) tackle this complementary challenge by proposing Quantum Trusted Execution Environments (QTEEs) hardware software co-designs that obscure user circuits from untrusted cloud providers or insider threats. Three architectures are introduced, QC-TEE, SoteriaQ, and CASQUE, employing techniques such as decoy control pulses and channel switching to obfuscate gate-level instructions. QTEEs are proposed as a hardware-viable alternative on current superconducting platforms, unlike blind quantum computation or quantum homomorphic encryption, which encounter significant hurdles. Their adaptation points towards the potential for commercial quantum services that ensure both data privacy and protection of algorithmic IP. 4 DEFINING QUANTUM-READY PRIMITIVES FOR HYBRID HPC–QC If secure and reliable execution are prerequisites, efficient hybridization is the key to practical performance gains. Delgado and Date (2025) address this by deconstructing Hamiltonian simulation workflows, central to fields from quantum chemistry to lattice gauge theory, into computational primitives. Each primitive is evaluated for its suitability for quantum offloading using metrics such as computational complexity, scalability, modularity, and physical relevance. The study shows that although state preparation and unitary evolution typically enjoy quantum speedup, tasks such as initial computation and post-processing are still optimally performed classically. The research outlines a strategy for modular hybrid workflows by aligning computational tasks with hardware capabilities, thereby optimizing throughput and reducing synchronization constraints. 5 ENGINEERING DEPENDABLE CLASSICAL–QUANTUM SYSTEMS Incorporating QPUs into HPC frameworks extends beyond enhancing performance and necessitates system-wide reliability. Giusto et al. (2025) discuss this through three interrelated pillars: reproducibility, resiliency, and security & privacy. They assert that QPUs, as unstable devices with error rates significantly higher than classical CPUs, generate shifting noise patterns that threaten reproducibility without intervention. A significant advancement is the use of the Hellinger distance as a statistical tool to assess reproducibility in probabilistic quantum outputs, establishing quantitative limits for variance in repeated runs to guide scheduling and device calibration. The study advocates for a cross-layer approach, from quantum hardware to middleware, emphasizing that dependable QHPC demands integrated physical robustness, workflow management, and cybersecurity solutions. A CONVERGING RESEARCH AGENDA Across these studies, several convergent themes are identified: • Hybrid Architectures Predominate Studies from Hamiltonian simulation to quantum optimization acknowledge that NISQ-era devices must involve classical-quantum coprocessing, establishing it as a long-term structural necessity. • Security and Assurance Trust in quantum computation must surpass algorithmic accuracy to cover the whole execution lifecycle, including protection against output tampering and securing proprietary methods. • Performance-Based Modularization Dividing processes into primitives facilitates selective quantum acceleration and mitigates the synchronization issues of complete quantum conversion. • Dependability as a Core Metric Incorporating reproducibility and resilience measures into early system design ensures that hybrid platforms reliably deliver consistent outcomes on a large scale. • Practicality over Perfection Acknowledging current quantum technology limits, approaches prioritize incremental, viable solutions like shot distribution, hardware obfuscation, and modular hybrid frameworks, instead of waiting for fully fault-tolerant systems. 6.1 From Patchwork Solutions to Integrated Frameworks Although each contribution addresses a different layer of the hybrid quantum–classical stack, the ultimate goal is integration. A future QHPC environment might: • Decompose workloads into quantum-ready primitives using frameworks like Delgado and Date. • Schedule and allocate primitives between classical and quantum resources with dependability metrics guiding the distribution. • Execute sensitive quantum modules within QTEEs to ensure confidentiality against untrusted providers. • Validate output integrity through adaptive multi-device shot distribution and statistical reproducibility analysis. • Feed back performance and trustworthiness metrics into system orchestration to continuously refine workload placement. Such an environment would be secure by design, performance aware, and resilient to both noise and adversarial interference. Achieving this vision will require collaboration across traditionally isolated communities: quantum algorithm developers, HPC systems engineers, hardware security architects, and statistical reliability researchers. 7 CONCLUSION The progression from experimental quantum systems to operational-grade hybrid high-performance computing systems is both a sociocultural and scientific challenge. The articles in this Research Topic collectively indicate a paradigm shift from proving quantum advantage in discrete tasks to establishing dependable, safe, and efficient frameworks for incorporating quantum processors into the global computing landscape. Key aspects such as hardware-based execution redundancy, cryptographic confidentiality, and cross-layer reliability are anticipated to substantially affect this transformative phase. The primary challenge is intricately fusing these diverse components to create a cohesive, scalable, and robust quantum-classical framework essential for converting theoretical insights into a practical computational model with revolutionary impacts on society.

  PublisherOA PDFDOI

• Modeling Short-Range Microwave Networks to Scale Superconducting Quantum Computation

  Quantum · 2025-01-08 · 7 citations

  articleOpen access

  A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributed quantum computing across small qubit arrays, known as chiplets, can address these challenges in a scalable manner. We propose a chiplet architecture over microwave links with potential to exceed monolithic performance on near-term hardware. Our methods of modeling and evaluating the chiplet architecture bridge the physical and network layers in these processors. We find evidence that distributing computation across chiplets may reduce the overall error rates associated with moving data across the device, despite higher error figures for transfers across links. Preliminary analyses suggest that latency is not substantially impacted, and that at least some applications and architectures may avoid bottlenecks around chiplet boundaries. In the long-term, short-range networks may underlie quantum computers just as local area networks underlie classical datacenters and supercomputers today.

  PublisherOA PDFDOI

• Access Improvements to Densely Packed Quantum Memory

  2025-08-30 · 1 citations

  articleSenior author

  Fault-tolerant quantum memory is essential for large-scale quantum computer systems and has recently achieved major experimental and theoretical advances. In 2023, McEwen, Bacon, and Gidney showed that walking code circuits move surface code logical qubits diagonally while maintaining comparable logical performance to standard surface code circuits. Building on this work, we apply gliding codes to create access hallways in densely packed qubit arrays using minimal ancilla space. This approach provides arbitrary access to stored qubits and supports cache-like eviction of qubits from the storage array. For a storage layout of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$l \times w$</tex> surface code logical qubits, our design reduces spacetime volume by <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$O(l w)$</tex> when compared to loose packings which allocate rows and columns of ancilla qubit patches between each logical qubit.

  PublisherDOI

• QuantEM: The quantum error management compiler

  ArXiv.org · 2025-09-19

  preprintOpen accessSenior author

  As quantum computing advances toward fault-tolerant architectures, quantum error detection (QED) has emerged as a practical and scalable intermediate strategy in the transition from error mitigation to full error correction. By identifying and discarding faulty runs rather than correcting them, QED enables improved reliability with significantly lower overhead. Applying QED to arbitrary quantum circuits remains challenging, however, because of the need for manual insertion of detection subcircuits, ancilla allocation, and hardware-specific mapping and scheduling. We present QuantEM, a modular and extensible compiler designed to automate the integration of QED codes into arbitrary quantum programs. Our compiler consists of three key modules: (1) program analysis and transformation module to examine quantum programs in a QED-aware context and introduce checks and ancilla qubits, (2) error detection code integration module to map augmented circuits onto specific hardware backends, and (3) postprocessing and resource management for measurement results postprocessing and resource-efficient estimation techniques. The compiler accepts a high-level quantum circuit, a chosen error detection code, and a target hardware topology and then produces an optimized and executable circuit. It can also automatically select an appropriate detection code for the user based on circuit structure and resource estimates. QuantEM currently supports Pauli check sandwiching and Iceberg codes and is designed to support future QED schemes and hardware targets. By automating the complex QED compilation flow, this work reduces developer burden, enables fast code exploration, and ensures consistent and correct application of detection logic across architectures.

  PublisherOA PDFDOI

• Heterogeneously error-corrected QRAMs

  ArXiv.org · 2025-04-30

  preprintOpen accessSenior author

  Quantum Random Access Memory (QRAM) holds the promise of enabling several large scale applications of quantum computers. However, designing fault tolerant QRAMs for large scale applications is still an open problem due to the poor error and resource scaling of current architectures. Existing protocols often overlook the need for error correcting QRAMs, which will be required for data-intensive, fault-tolerant applications. However, naively error correcting all qubits used to implement the QRAM is prohibitively resource intensive, quickly becoming infeasible for large applications. To fill this gap, we propose a novel QRAM architecture that leverages variable strength error correction. We strongly error-correct qubits that heavily influence query fidelity, and lightly correct less critical regions of the QRAM. This scheme produces queries with fidelity bounded by a constant for arbitrarily sized QRAMs without requiring improvements in physical hardware. Furthermore, the heterogeneous scheme requires 5x fewer resources (for depth 30 QRAM) and quadratically slower error scaling as compared to a uniformly error corrected Bucket Brigade QRAM. In this work, we present a rigorous analysis of the query fidelity scaling and perform resource analyses of two variations of the heterogeneous architecture using the surface code. We verify our results using numerical simulations and compare our results against several other existing QRAM techniques. Through our results, we quantitatively prove the optimal scaling of the heterogeneous architecture, paving a way for data-intensive and fault tolerant quantum applications.

  PublisherOA PDFDOI

Frequent coauthors

• Frederic T. Chong

  University of Chicago

  52 shared

• Elena Zaitseva

  University of Žilina

  49 shared

• Martin Lukáč

  49 shared

• Krzysztof Podlaski

  49 shared

• Shinobu Nagayama

  Hiroshima City University

  49 shared

• Gokul Subramanian Ravi

  38 shared

• Mitchell A. Thornton

  26 shared

• Jonathan M. Baker

  19 shared

Labs

• Kevin Smith LabPI