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Robert Wille

Publications and source records attributed to Robert Wille.

At least 19 recordsLinked to original sources
arXiv2026

Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems

High Performance Computing-Quantum Computing (HPCQC) platforms expose multiple Quantum Processing Units (QPUs) that may differ in size, topology, native gates, and noise characteristics. For current noisy devices, errors compound along the compiled circuits quickly, and minimizing them, that is, maximizing the circuits' execution fidelity, is essential for reliable results. Fidelity depends on the compilation to a specific target device: the same high-level circuit may produce different executables and, therefore, different expected fidelities across QPUs. We present a low-overhead fidelity-aware scheduling framework for multi-QPU systems based on a Graph Neural Network (GNN) that estimates, before compilation, the expected fidelity of each circuit on each available QPU. Then, a tunable scheduler uses these estimates to control the trade-off between execution fidelity and parallelism. Results show that this framework allows for approximating an exhaustive fidelity-based assignment, saving computational resources compared to a brute-force approach that compiles each circuit on every device.

quant-ph↗
arXiv2026

Shuttling-aware dynamical decoupling for quantum charge-coupled devices

Dynamical decoupling (DD) helps maintain high-fidelity quantum computations by suppressing dephasing noise through carefully timed refocusing pulses. In quantum charge-coupled device (QCCD) architectures, however, where ions are shuttled throughout the device, transport constrains when pulses can be applied and affects the phase accumulated by an ion. Conventional DD methods do not account for shuttling and may therefore schedule pulses that must be omitted or shifted after transport scheduling, weakening the protection from dephasing. We therefore introduce shuttling-aware dynamical decoupling (SADD), an offline compiler pass that jointly selects refocusing pulses and local ion rerouting while preserving logical-gate timings and the total schedule length. In benchmark simulations, SADD improves average final-state fidelity over both the original schedules and a simple nearest-feasible Hahn-echo baseline when dephasing dominates control and transport errors and varies slowly enough for DD. Rerouting enables otherwise infeasible pulse timings, while spatial information about the noise can provide further gains. These benefits disappear, however, when the added transport introduces too much error. Overall, our results show that coordinating DD with ion transport is an effective compiler strategy for reducing dephasing in QCCD processors.

quant-ph↗
arXiv2026

Scalable Lindblad Noise Learning via Stochastic Tensor-Network Simulation

Learning dissipation rates in large-scale open quantum systems is a major obstacle for near-term quantum technologies, as existing Lindblad estimation methods are typically limited to small system sizes due to the computational complexity of repeatedly solving the Lindblad equation during optimization. Here, we propose a scalable noise-learning framework for Lindblad dissipation rates that combines a stochastic simulation method, the Tensor Jump Method (TJM), with gradient-free optimization of a least-squares cost-function defined on time series of local-observable expectation values. We demonstrate the approach on two noise models in the Ising model: a site-resolved (local) model, in which independent dissipation rates are learned for each site up to $N_{\mathrm{site}}=16$, and a spatially homogeneous (global) model with only seven parameters, scaled to $N_{\mathrm{site}}=160$ sites.We complement these numerical results with a series of exact, provable guarantees: the Frobenius variance of the TJM density-matrix estimator is shown to equal $(1-\mathrm{Tr}[\rho^2])/N_{\mathrm{traj}}$, an exact purity-based characterization of the stochastic estimation error; the corresponding purity evolution is proven to be monotonically non-increasing for Hermitian jump operators; and, under a finite covariance distance assumption, the standard deviation of the cost-function is shown to decrease with system size, so that fewer trajectories are needed to reach a fixed target accuracy as the system grows. Together, this combination of scalable numerics and rigorous theoretical guarantees positions TJM-based noise learning as a practical foundation for characterizing dissipation in large quantum devices and for guiding future work on error mitigation and quantum error correction.

quant-ph↗
arXiv2026

Know Your Qubits, Know Your Users: Personas for Quantum Software

The advancement of quantum hardware and the intricacies of quantum computing make well-designed quantum software increasingly necessary. Due to the interdisciplinarity of the field, it is crucial to understand the perspectives and specific needs of involved stakeholders, for example, to balance the desired level of abstraction with the exposition of (hardware)-specific details. In this work, we conduct a stakeholder-based analysis to identify personas of quantum software as a means of creating meaningful, user-tailored quantum software. We conducted an expert focus group at a Dagstuhl seminar in 2024 and qualitative interviews with practitioners at conference IEEE QCE in 2025, from which we derive eleven personas of potential users and stakeholders for quantum software. We discuss these personas regarding their use cases, interests, constraints and abstraction level.

quant-ph↗
arXiv2026

Teaching Quantum Design Automation with Block-Based Programming

As quantum circuits grow beyond small toy examples, preparing them for execution on physical devices becomes increasingly complex. Design automation is therefore essential for scalable quantum computing: Compilation procedures optimize resource requirements and transform circuits to a format compatible with specific hardware; resource estimation evaluates execution cost; verification methods prove circuit correctness. However, these concepts present a steep learning curve for novices, particularly when quantum circuits are introduced through low-level textual representations. To address this, we present a block-based programming framework for quantum design automation, implemented as an extension to the Scratch programming platform. This system allows users to build quantum circuits as a sequence of blocks and embed them in classical control logic to perform evaluations, compare simulation results, and directly apply different design automation techniques. We evaluated the approach in a user study with computer science students, who completed guided exercises using the platform and provided structured feedback in the form of self-reports and short knowledge assessments. Results demonstrate strong understanding and confidence in quantum design automation concepts, suggesting that the block-based approach successfully lowers the entry barrier to quantum design automation. The implemented framework is open-source and available at https://github.com/munich-quantum-toolkit/scratch-quantum.

physics.ed-ph↗
arXiv2026

Basis-update and Galerkin time integration in canonical matrix-product-state form

Matrix product state algorithms must enlarge their bond spaces as entanglement grows and compress them to control cost. We formulate basis-update and Galerkin (BUG) time integration as a sequence of canonical MPS sweeps for Hamiltonians represented as matrix product operators. We show when two natural basis updates produce the same trial space and when transporting coefficients between successive bases preserves the represented state. Under these conditions, the existing first-order error bound for uncompressed tree-tensor-network BUG also applies to the alternating-endpoint MPS schedule. We verify the uncompressed implementation against an independent six-site calculation. We then compare BUG with two-site TDVP for 16-site transverse-field Ising and Haldane-Shastry dynamics. At matched timestep and truncation settings, BUG performs fewer local exponential actions and has lower runtime. These settings do not produce equal accuracy. The runtime versus accuracy curves cross for the Ising model and are close for the Haldane-Shastry model. The comparison therefore identifies model-dependent trade-offs rather than a general advantage for either method.

quant-ph↗
arXiv2026

Scalable Circuit Cutting: A Framework for Combined Gate and Wire Cuts Using Gate Groups

Quantum circuit cutting enables the execution of large circuits on devices with a limited number of qubits by partitioning circuits into independent subcircuits. However, this introduces a sampling overhead, which grows exponentially with the number of cuts, rendering the choice of cut placements critical for practical circuit cutting. Determining optimal cut placements remains computationally challenging, particularly as circuits grow in size. Additionally, existing circuit cutting approaches typically treat gate and wire cuts independently. Those combining both cutting approaches, however, do not take advantage of joint cutting, i.e., identifying common gate groups and cutting them jointly for a reduced overhead. This work presents a unified framework that combines gate and wire cutting within a single partitioning strategy, enabling more efficient circuit decompositions. Moreover, our approach incorporates joint cutting via a novel gate grouping technique, further reducing sampling overhead. By formulating the cut placement problem as a scalable graph partitioning task, our method efficiently identifies near-optimal cut placements for large circuits, also providing diagnostic feedback on whether circuits are suitable for cutting.

quant-ph↗
arXiv2026

Guiding Compiler Optimizations for Neutral Atom Quantum Computers Through Visualizations

The scale of Neutral Atom (NA) quantum computers requires automated compilation tools. Designing the required heuristic methods demands a deep understanding of complex hardware trade-offs, for which visualizations can provide crucial insights. This work introduces NAViz, the first publicly available app to visualize quantum computations on NA devices in real-time. A case study demonstrates how NAViz was instrumental in identifying and resolving inefficiencies in an existing compilation strategy, leading to a new, more performant one. The tool is available as part of the Munich Quantum Toolkit (MQT) at https://github.com/munich-quantum-toolkit/naviz.

quant-ph↗
arXiv2026

Enabling Neutral Atom Integration: Redesigning Device Models for Universal Quantum Ecosystems

Quantum computing is transitioning from an academic idea to a practical technology, driven by recent hardware advancements and clear paths toward real-world applications. Universal quantum ecosystems (e.g., Qiskit, Cirq, PennyLane) facilitate this transition by providing a consistent interface to diverse quantum devices, abstracting hardware-specific details through a device model that captures each device's computational capabilities. However, these device models have historically been shaped by superconducting hardware, assuming static qubit positions and fixed coupling maps. This prevents them from representing the unique computational capabilities of emerging technologies such as neutral atoms, which feature dynamic qubit rearrangement and zoned operations. As a result, although numerous specialized compilers for neutral atom devices already exist, they cannot retrieve the hardware information they need through these ecosystems - creating a technology lock that hinders or even prevents the integration of neutral atom devices. In this work, we demonstrate how this limitation leads to suboptimal compilation results and can exclude certain devices entirely. Motivated by this, we propose rethinking current device models to faithfully represent neutral atom devices, enabling their seamless integration into universal quantum ecosystems. Evaluations conducted within the Quantum Device Management Interface (QDMI) demonstrate that the proposed device model unlocks a routing overhead fidelity improvement by a factor of up to 100,000 on a circuit with 16 qubits and 600 gates.

quant-ph↗
arXiv2026

Routing Techniques for Error-Corrected Silicon Spin Qubit Quantum Architectures

Silicon spin qubits have emerged as a promising qubit technology due to their favorable scaling and fabrication properties. However, efficiently compiling quantum circuits onto spin qubit platforms remains challenging, particularly when accounting for hardware constraints and the high sensitivity to static defects. Existing compilation approaches for spin qubits either largely ignore error correction, despite its critical role for large-scale quantum computation, or focus on low-level schedule constructions, missing a high-level compilation and routing for logical, error-corrected algorithms. To address this gap, we introduce a compilation framework for spin qubits based on the recent snakes on a plane model, which utilizes a 2D surface code and qubit teleportation to mitigate errors. Building on this model, we propose shortest-path and rotation-based algorithms as two novel classes of qubit-routing techniques, along with additional defect-handling and initial-mapping strategies. We evaluate both algorithms across diverse architectural settings and problem sizes, demonstrating that shortest-path methods excel in sparse, low-defect scenarios, while rotation-based approaches perform better in high-density environments. An open-source implementation of our framework is publicly available on GitHub as part of the Munich Quantum Toolkit (MQT) at https://github.com/munich-quantum-toolkit/spin-qubit-routing.

quant-ph↗
arXiv2026

Complementary 3D color codes for transversal quantum logic

Transversal logical gates provide a direct route to fault-tolerant quantum computation, but the Eastin-Knill theorem forbids a universal transversal gate set within a single quantum error-correcting code. We propose a hybrid architecture based on the tetrahedral three-dimensional color code and its Hadamard-transformed counterpart, which we call the H-tetrahedral code. The two encodings support complementary transversal non-Clifford operations. Combined with bitwise Hadamard transformations that switch between the two encodings and a one-way transversal logical CNOT from the tetrahedral code to the H-tetrahedral code, these operations realize an almost-universal transversal logical gate set that enables both the creation of entanglement and logical states with magic. We complete a universal gate set through a pieceably fault-tolerant round-robin construction of a logical controlled-$Z$ gate between two H-tetrahedral codes. This logical entangling gate is interleaved with reduced-overhead Steane-type syndrome extraction using logical two-dimensional color-code auxiliary qubits. Our construction provides a new route toward implementing classically hard-to-simulate quantum algorithms where magic and most entangling operations are transversal while the resource overhead is concentrated in a small number of non-transversal Clifford entangling operations.

quant-ph↗
arXiv2026

Towards Lattice Surgery Compilation for the Color Code Using Pipe Diagrams

Pipe diagrams have emerged as a powerful framework for flexible lattice surgery compilation and spacetime optimization for the surface code. In contrast, analogous compilation techniques for color code architectures remain largely unexplored, despite the color code's favorable properties, including reduced qubit overhead and transversal single-qubit Clifford gates. In this work, we develop a pipe diagram representation for the triangular color code on the 6.6.6 lattice and establish its correspondence to ZX-diagrammatic descriptions of computation. We present distance-independent constructions of color code pipe diagrams together with explicit realizations of correlation surfaces, stabilizers, and syndrome extraction circuits. This framework enables both macroscopic optimization of logical computations in spacetime and microscopic compilation to executable syndrome extraction circuits. We demonstrate the potential for compact spacetime embeddings with the color code's geometry. These results provide a foundation for automated lattice surgery compilation and diagrammatic optimization in color code architectures.

quant-ph↗
arXiv2026

Noisy quantum circuit simulation with the tensor jump method

Classical simulation of noisy quantum circuits is essential for validating algorithms, benchmarking hardware, and assessing error-mitigation strategies, but remains limited by the exponential cost of density-matrix methods and the high variance of standard trajectory sampling. We introduce a variance-aware tensor network framework that combines the tensor jump method with local TDVP gate evolution on matrix product states and sparse Pauli-Lindblad hardware noise models. Gates are applied as short variational evolutions on the MPS manifold, while noise is sampled per circuit window from Pauli-Lindblad jump sets with state-independent hazards and dissipative contractions that reduce to irrelevant global factors after renormalization. The method supports correlated multi-qubit Lindblad noise consistent with hardware connectivity, including long-range operators on non-adjacent qubits, enabling direct simulation of crosstalk and other connectivity-induced errors beyond local noise models. We develop two unbiased variance-aware unravelings. An analog unitary-mixture unraveling matches the Lindblad generator exactly under symmetric Gaussian or two-point angle laws, while a projector-jump unraveling yields state-independent hazards and closed-form variance laws. Both retain the standard 1/sqrt(N) Monte Carlo convergence but with reduced prefactors. Empirically, projector sampling strongly reduces trajectory variance and bond-dimension growth across many circuit architectures, whereas analog sampling is most effective at weak noise. We demonstrate accurate, scalable noisy-circuit simulation on a 25-qubit noisy XY quench and IBM's 127-qubit kicked-Ising benchmark with long-range depolarizing noise, achieving reduced Monte Carlo variance and favorable MPS bond-dimension growth compared with standard Kraus-insertion baselines.

quant-ph↗
arXiv2026

MLIR for Quantum Beyond Gate Cancellation: Quantum Circuit Mapping Reimagined

The Multi-Level Intermediate Representation (MLIR) framework has become a cornerstone for building extensible, domain-specific compilers, with the quantum computing community already leveraging it to model quantum programs and implement basic optimizations. However, computationally intensive tasks in the quantum compilation pipeline, such as quantum circuit mapping, remain underexplored within the MLIR ecosystem. This paper proposes an MLIR-native blueprint for these non-local, quantum-specific optimization routines by reimplementing a well-established, state-of-the-art mapping A* search algorithm for qubit routing and SWAP insertion. Our evaluation demonstrates that this approach not only integrates seamlessly into an MLIR-based quantum compiler collection but also surpasses previous non-MLIR solutions in both solution quality and runtime. The implementation is open-source and publicly available at https://github.com/munich-quantum-toolkit/core.

quant-ph↗
arXiv2026

Computational regimes in matrix-product-state-based quantum trajectory simulations

Efficient simulation of open quantum systems is central to modeling noisy quantum hardware and many-body dynamics. In trajectory-based tensor network methods, cost is often associated with trajectory-level quantities such as entanglement growth or bond dimension. However, the total cost of a fixed-accuracy simulation also depends on statistical sampling, and the interplay between per-trajectory complexity and sampling effort remains poorly understood. Here we introduce a cost-resolved framework for matrix product state (MPS)-based quantum trajectory simulations that decomposes total cost into memory per trajectory, runtime per trajectory, and sampling effort. We show that physically equivalent stochastic unravelings of the same Lindblad dynamics do not necessarily reduce total cost, but instead redistribute cost between trajectory complexity and statistical convergence. This trade-off is quantified by two dimensionless inflation factors: a bond dimension inflation $\alpha$ and a sampling inflation $\kappa$, which together determine the preferred unraveling under hardware-dependent memory and parallelism constraints. We provide a practical protocol for extracting $(\alpha,\kappa)$ from modest pilot simulations and demonstrate it using benchmarks across multiple noise channels. The resulting decision maps show that the computationally favorable unraveling can change with noise strength, time-step resolution, system size, and available parallelism. These results establish unraveling choice as a hardware-aware simulation design problem rather than an intrinsic optimization of trajectory entanglement alone.

quant-ph↗
arXiv2026

Automatic De-Quantization of Quantum Programs Using Constant Propagation

Quantum computing promises to solve problems beyond the reach of classical computers, but today's quantum hardware is error-prone and much slower than classical hardware. Every quantum operation is costly, making it crucial to minimize quantum resource usage in near-term algorithms. Quantum resources should only be used when they are truly essential for quantum advantage, and not wasted on operations that can be efficiently handled by classical computation. In this work, we focus on de-quantizing quantum operations to classical computation whenever possible. The approach we propose for this is hybrid quantum-classical constant propagation, an optimization which reduces quantum operations by trading them for fast, reliable classical instructions. This is done by tracking between quantum and classical states to identify and eliminate unnecessary quantum gates and controls. We formalize a hybrid state model for quantum-classical constant propagation, implement our optimizations in the open-source MQT Core tool, and evaluate them on benchmark circuits. The obtained results show that quantum-classical constant propagation can reduce costly multi-qubit operations, making quantum programs more practical and robust for near-term devices. This opens the door to new hybrid compiler strategies that leverage the best of both quantum and classical worlds.

quant-ph↗
arXiv2026

Synthesis and Optimization of Encoding Circuits for Fault-Tolerant Quantum Computation

Preparing arbitrary logical states is a central primitive for universal fault-tolerant quantum computation and the cost of encoded-state preparation contributes directly to the overall resource overhead. This makes the synthesis of efficient general-state encoding circuits an important problem, particularly with respect to two-qubit gate count and circuit depth. Yet the synthesis of such encoders has been studied less extensively than general Clifford circuit synthesis or the preparation of specific logical Pauli-eigenstates. In this work, we develop methods for synthesizing efficient encoders for arbitrary stabilizer codes. We formulate encoder synthesis as a search over stabilizer tableaus and introduce greedy and rollout-based algorithms that exploit the freedom among stabilizer-equivalent realizations of the same encoding isometry. For code families with a modular structure, such as generalized concatenated and holographic codes, we show how large encoders can be assembled from optimized local constituent encoders, and we use SMT-based exact synthesis to obtain optimal local circuits for small instances. We further evaluate the proposed methods on a broad set of stabilizer codes, including holographic and quantum low-density parity-check (qLDPC) codes, and compare them against recent encoder-synthesis methods and existing constructions from the literature, obtaining improvements of up to 43% in two-qubit gate count and up to 70% in depth. Our results support the optimization of encoded-state preparation in several fault-tolerant quantum-computing schemes, and all methods are openly available as part of the Munich Quantum Toolkit.

quant-ph↗
arXiv2026

Practical HPCQC Integration with QDMI: A Real-Hardware Case Study with IQM Systems

Quantum computers are moving into HPC centers, and the main challenge is now integration rather than pure hardware access. Many current software paths still depend on vendor-specific adapter chains between user SDKs, schedulers, and backend APIs. This pattern makes operations more complex than necessary and slows the transition from pilots to production workflows. We present a practical integration path centered on the Quantum Device Management Interface (QDMI). Using IQM superconducting systems as a hardware case study, we implement an IQM-backed QDMI layer and connect it to two software layers that HPC centers working with quantum computers already care about: Slurm-based job execution and Qiskit-facing user workflows. The implementation is publicly available at https://github.com/iqm-finland/QDMI-on-IQM. The key message is simple: integrating quantum hardware into HPC does not have to be a bespoke engineering effort for each backend. Once the software-hardware boundary is standardized, large parts of the stack become reusable across providers and deployment styles. Our results do not claim that standardization eliminates all HPCQC challenges. They show that this specific boundary can already be standardized today in a way that is practical for users, operators, and vendors.

quant-ph↗