About

Christopher Monroe is the Gilhuly Family Presidential Distinguished Professor in the Departments of Electrical and Computer Engineering (ECE) and Physics at Duke University. He serves as the Principal Investigator of the Quantum Computing with Trapped Ions research group. His work focuses on quantum computing using trapped ions, encompassing quantum circuit applications, quantum simulation of many-body physics, quantum computer system design and fabrication, and ion-photonic quantum networks. Monroe leads a multidisciplinary team including research professors, postdoctoral associates, graduate students, and undergraduate researchers, all contributing to advancing the field of quantum information science. His lab is located in the Chesterfield building at Duke University, where he also maintains an office and oversees multiple research spaces dedicated to experimental quantum computing.

Research topics

• Computer Science
• Physics
• Quantum mechanics
• Statistical physics
• Engineering
• Algorithm
• Mathematics
• Artificial Intelligence
• Political Science
• Library science
• Electrical engineering
• Theoretical computer science
• Applied mathematics
• Telecommunications
• Computer architecture
• Computational science
• Public relations
• Engineering physics
• Condensed matter physics
• History
• Atomic physics
• Data science
• Engineering ethics
• Mathematical optimization

Selected publications

• Nonlocal Games as Cross-Platform Quantum Benchmarks: Exceeding unconditional classical bounds on trapped-ion processors

  arXiv (Cornell University) · 2026-03-18

  preprintOpen access

  Nonlocal games provide application-level benchmarks for quantum hardware whose classical performance bounds are information-theoretic, holding against all classical strategies regardless of computational resources. We implement a 14-vertex graph coloring game, the smallest graph exhibiting a quantum-classical separation for this game type, on four trapped-ion quantum processors across three institutions. One system achieved a win rate that surpasses the classical bound with statistical significance, marking the first violation of a classical bound in a graph coloring nonlocal game on quantum hardware. The remaining systems achieved win rates comparable to the best superconducting processors evaluated on the same game, further illustrating the potential of nonlocal games as cross-architecture quantum benchmarks.

  PublisherDOI

• Nonlocal Games as Cross-Platform Quantum Benchmarks: Exceeding unconditional classical bounds on trapped-ion processors

  ArXiv.org · 2026-03-18

  articleOpen access

  Nonlocal games provide application-level benchmarks for quantum hardware whose classical performance bounds are information-theoretic, holding against all classical strategies regardless of computational resources. We implement a 14-vertex graph coloring game, the smallest graph exhibiting a quantum-classical separation for this game type, on four trapped-ion quantum processors across three institutions. One system achieved a win rate that surpasses the classical bound with statistical significance, marking the first violation of a classical bound in a graph coloring nonlocal game on quantum hardware. The remaining systems achieved win rates comparable to the best superconducting processors evaluated on the same game, further illustrating the potential of nonlocal games as cross-architecture quantum benchmarks.

  PublisherOA PDF

• Quantum Machine Learning via Contrastive Training

  ArXiv.org · 2025-11-17

  preprintOpen accessSenior author

  Quantum machine learning (QML) has attracted growing interest with the rapid parallel advances in large-scale classical machine learning and quantum technologies. Similar to classical machine learning, QML models also face challenges arising from the scarcity of labeled data, particularly as their scale and complexity increase. Here, we introduce self-supervised pretraining of quantum representations that reduces reliance on labeled data by learning invariances from unlabeled examples. We implement this paradigm on a programmable trapped-ion quantum computer, encoding images as quantum states. In situ contrastive pretraining on hardware yields a representation that, when fine-tuned, classifies image families with higher mean test accuracy and lower run-to-run variability than models trained from random initialization. Performance improvement is especially significant in regimes with limited labeled training data. We show that the learned invariances generalize beyond the pretraining image samples. Unlike prior work, our pipeline derives similarity from measured quantum overlaps and executes all training and classification stages on hardware. These results establish a label-efficient route to quantum representation learning, with direct relevance to quantum-native datasets and a clear path to larger classical inputs.

  PublisherOA PDFDOI

• Simulating Meson Scattering on Spin Quantum Simulators

  Quantum · 2025-06-17 · 12 citations

  articleOpen access

  Studying high-energy collisions of composite particles, such as hadrons and nuclei, is an outstanding goal for quantum simulators. However, preparation of hadronic wave packets has posed a significant challenge, due to the complexity of hadrons and the precise structure of wave packets. This has limited demonstrations of hadron scattering on quantum simulators to date. Observations of confinement and composite excitations in quantum spin systems have opened up the possibility to explore scattering dynamics in spin models. In this article, we develop two methods to create entangled spin states corresponding to wave packets of composite particles in analog quantum simulators of Ising spin Hamiltonians. One wave-packet preparation method uses the blockade effect enabled by beyond-nearest-neighbor Ising spin interactions. The other method utilizes a quantum-bus-mediated exchange, such as the native spin-phonon coupling in trapped-ion arrays. With a focus on trapped-ion simulators, we numerically benchmark both methods and show that high-fidelity wave packets can be achieved in near-term experiments. We numerically study scattering of wave packets for experimentally realizable parameters in the Ising model and find inelastic-scattering regimes, corresponding to particle production in the scattering event, with prominent and distinct experimental signals. Our proposal, therefore, demonstrates the potential of observing inelastic scattering in near-term quantum simulators.

  PublisherOA PDFDOI

• Floquet control of interactions and edge states in a programmable quantum simulator

  Nature Communications · 2025-10-03 · 3 citations

  articleOpen accessSenior author

  Quantum simulators based on trapped ions enable the study of spin systems and models with rich dynamical phenomena. The Su-Schrieffer-Heeger (SSH) model for fermions in one dimension is a canonical example that can support a topological insulator phase when couplings between sites are dimerized, featuring long-lived edge states. Here, we experimentally implement a spin-based variant of the SSH model using one-dimensional trapped-ion chains with tunable interaction range, realized in crystals containing up to 22 interacting spins. Using an array of individually focused laser beams, we apply site-specific, time-dependent Floquet fields to induce controlled bond dimerization. Under conditions that preserve inversion symmetry, we observe edge-state dynamics consistent with SSH-like behavior. We study the propagation and localization of spin excitations, as well as the evolution of highly excited configurations across different interaction regimes. These results demonstrate how precision Floquet engineering enables the exploration of complex spin models and dynamics, laying the groundwork for future preparation and characterization of topological and exotic phases of matter.

  PublisherOA PDFDOI

• High-fidelity remote entanglement of trapped atoms mediated by time-bin photons

  Nature Communications · 2025-03-14 · 28 citations

  articleOpen accessSenior author

  Photonic interconnects between quantum processing nodes are likely the only way to achieve large-scale quantum computers and networks. The bottleneck in such an architecture is the interface between well-isolated quantum memories and flying photons. We establish high-fidelity entanglement between remotely separated trapped atomic qubit memories, mediated by photonic qubits stored in the timing of their pulses. Such time-bin encoding removes sensitivity to polarization errors, enables long-distance quantum communication, and is extensible to quantum memories with more than two states. Using a measurement-based error detection process and suppressing a fundamental source of error due to atomic recoil, we achieve an entanglement fidelity of 97% and show that fundamental limits due to atomic recoil still allow fidelities in excess of 99.9%.

  PublisherOA PDFDOI

• In-situ mid-circuit qubit measurement and reset in a single-species trapped-ion quantum computing system

  ArXiv.org · 2025-04-17

  preprintOpen access

  We implement in-situ mid-circuit measurement and reset (MCMR) operations on a trapped-ion quantum computing system by using metastable qubit states in $^{171}\textrm{Yb}^+$ ions. We introduce and compare two methods for isolating data qubits from measured qubits: one shelves the data qubit into the metastable state and the other drives the measured qubit to the metastable state without disturbing the other qubits. We experimentally demonstrate both methods on a crystal of two $^{171}\textrm{Yb}^+$ ions using both the $S_{1/2}$ ground state hyperfine clock qubit and the $S_{1/2}$-$D_{3/2}$ optical qubit. These MCMR methods result in errors on the data qubit of about $2\%$ without degrading the measurement fidelity. With straightforward reductions in laser noise, these errors can be suppressed to less than $0.1\%$. The demonstrated method allows MCMR to be performed in a single-species ion chain without shuttling or additional qubit-addressing optics, greatly simplifying the architecture.

  PublisherOA PDFDOI

• Photonic Networking of Quantum Memories in High-Dimensions

  ArXiv.org · 2025-05-16

  preprintOpen accessSenior author

  Quantum networking enables the exchange of quantum information between physically separated quantum systems, which has applications ranging from quantum computing to unconditionally secure communication. Such quantum information is generally represented by two-level quantum systems or qubits. Here, we demonstrate a quantum network of high-dimensional (HD) quantum memories or ``qudits" stored in individual atoms. The interference and detection of HD time-bin encoded single photons emitted from atomic qudit memories heralds maximally-entangled Bell states across pairs of atomic qudit levels. This approach expands the quantum information capacity of a quantum network while improving the entanglement success fraction beyond the standard 50\% limit of qubit-based measurement protocols.

  PublisherOA PDFDOI

• Observation of a finite-energy phase transition in a one-dimensional quantum simulator

  Nature Physics · 2025-01-17 · 15 citations

  articleSenior author
  PublisherDOI

• Non-invasive mid-circuit measurement and reset on atomic qubits

  arXiv (Cornell University) · 2025-04-17

  preprintOpen access

  Mid-circuit measurement and reset of subsets of qubits is a crucial ingredient of quantum error correction and many quantum information applications. Measurement of atomic qubits is accomplished through resonant fluorescence, which typically disturbs neighboring atoms due to photon scattering. We propose and prototype a new scheme for measurement that provides both spatial and spectral isolation by using tightly-focused individual laser beams and narrow atomic transitions. The unique advantage of this scheme is that all operations are applied exclusively to the read-out qubit, with negligible disturbance to the other qubits of the same species and little overhead. In this letter, we pave the way for non-invasive and high fidelity mid-circuit measurement and demonstrate all key building blocks on a single trapped barium ion.

  PublisherOA PDFDOI

Recent grants

• Collaborative: Photonic Quantum Networking of Trapped Ion Qubits

  NSF · $387k · 2007–2009

• Photonic Quantum Networking of Trapped Ion Qubits

  NSF · $480k · 2009–2013

Frequent coauthors

• Norbert Linke

  220 shared

• Daiwei Zhu

  IonQ (United States)

  198 shared

• K. A. Landsman

  University of Maryland, College Park

  172 shared

• Alexey V. Gorshkov

  170 shared

• Guido Pagano

  152 shared

• Marko Cetina

  144 shared

• David Hayes

  140 shared

• Peter Maunz

  IonQ (United States)

  139 shared

Labs

• Duke University Quantum Computing with Trapped IonsPI

Education

• Ph.D., Physics

  University of California, Berkeley

  1994

• B.S., Physics

  University of California, Berkeley

  1989

Awards & honors

• Elected Member. National Academy of Sciences (2016)