arXiv subjects

Wolfgang Lechner

Publications and source records attributed to Wolfgang Lechner.

At least 19 recordsLinked to original sources

arXiv2026

From NISQ to Fault-Tolerance: Applications and Algorithmic Benchmarks for Spin Qubits

Motivated by recent breakthroughs in the development of spin-based quantum processing units based on exchange-only (EO) spin qubits, we provide a roadmap for the implementation of quantum algorithms on the EO platform, ranging from the NISQ to the fault-tolerant era. To provide an algorithm-driven perspective on the scaling of quantum chips, we consider a range of applications targeting different stages of hardware maturity and formulate requirements for a successful realization. We show that the compilation method Parity Twine perfectly complements the hardware's capabilities to perform tasks such as the quantum Fourier transform or QAOA. Furthermore, we describe an error detection technique native to Parity Twine, which EO qubits can leverage in a unique and advantageous way to improve algorithm performance. Finally, since both near-term algorithmic benchmarks and a long-term perspective can be found in digital quantum simulation, we specifically discuss the fermionic fast Fourier transform and the simulation of Fermi-Hubbard models. The latter is explicitly discussed in the context of quantum error correction and a partially fault-tolerant realization. By providing detailed resource estimates and identifying scaling bottlenecks on each level, our work offers a quantitative perspective on EO-based quantum computing and will inform future hardware design choices.

quant-ph↗

arXiv2026

Quantum Optimisation for Protein-Protein Interaction Network Alignment

Protein-protein interaction (PPI) network alignment combines topological and sequence information to identify conserved modules across species, but global alignment remains challenging: heuristics sacrifice optimality, while exact methods lack scalability. We model the alignment as a weighted maximum common induced subgraph problem and reformulate it through the modular product graph to a minimum-weight vertex cover on the complement, with node weights carrying sequence similarity. To solve this problem, we develop a hybrid framework combining kernelisation, branch-and-bound, and seven Quantum Approximate Optimisation Algorithm (QAOA) formulations. These formulations differ in how the cover constraints are enforced, from penalty terms in the cost Hamiltonian to mixers confined to the feasible subspace. For single round QAOA, we derive closed-form expressions for the expected cost of four circulant mixer variants, enabling performance characterisation without circuit simulation. Applied to synthetic and real-world networks reduced to KEGG pathways, the QAOA formulations achieve high topological conservation on the aligned core while at least maintaining biological conservation comparable to leading classical aligners, at the cost of reduced node coverage. Across selected KEGG pathways, the aligned subnetworks retain disease-associated proteins, preserving biologically relevant information. Cheaper formulations leave more edges uncovered, while enforcing feasibility in the mixer raises circuit depth by one to two orders of magnitude. Together, these results highlight the potential of quantum optimisation for PPI network alignment and the resource trade-offs that will shape its scalability as quantum hardware matures.

quant-ph↗

arXiv2026

Optimizing Atom Transport, Gate-Count and Depth with Parity Twine

We present an efficient implementation of the Parity Architecture for neutral-atom quantum processors. We adapt Parity Twine Networks (PTNs) to different atom layouts, native entangling gates, and atom-shuttling capabilities. This provides a general framework for hardware-aware optimization of gate count, circuit depth, and atom transport for quantum circuits encoding arbitrary interaction graphs in a common basis. Specifically, we develop PTN constructions based on different native entangling-gate realizations, namely CZ, CZSWAP, and iSWAP, providing flexibility to accommodate different hardware capabilities on both static and mobile neutral-atom platforms. Using the quantum Fourier transform (QFT) as a representative example, we demonstrate substantial reductions in two-qubit gate count, atom transport, and circuit depth. These resource savings translate into an estimated circuit fidelity three orders of magnitude higher than competing compilation strategies for a 30-qubit QFT. We further extend the construction to the recently introduced optimistic QFT and discuss the broader applicability of PTNs to other quantum algorithms on neutral-atom platforms.

quant-ph↗

arXiv2026

Parity Mapping for Quantum Optimization on Frustrated Ising Rings

The frustrated Ising ring is one of the simplest models exhibiting exponential closing spectral gaps, making it a paradigmatic and challenging benchmark for quantum annealing (QA). Ground-state preparation for this model has therefore been studied extensively in both continuous-time QA and digitized protocols such as the Quantum Approximate Optimization Algorithm (QAOA). Here, we use the frustrated Ising ring to investigate how the parity mapping affects the performance of both QA and QAOA. For QA, finite-size calculations show that the parity mapping increases the minimum spectral gap under the energy normalization used in this work, thereby enabling faster continuous-time ground state preparation protocols. An ideal implementation of Parity-QA, with a single global constraint, shows no evidence of exponential gap closing over the accessible system sizes, whereas a hardware-motivated decomposition into local constraints restores the exponential decrease, albeit with a smaller fitted exponent than conventional QA. For the digitized protocol, we find that the number of Parity-QAOA layers required to prepare the exact ground state remains constant over the simulated sizes, improving upon the quadratic scaling required by conventional QAOA. To investigate the role of constraints in Parity-QAOA, we further consider a modified Ising ring instance in which the constraint term is essential for preparing the target ground state. We then compare the corresponding resource requirements with those of conventional QAOA.

quant-ph↗

arXiv2026

Qudit extension of parameterized IQP circuits: A generative quantum machine learning approach to integer data

Parameterized Instantaneous Quantum Polynomial (IQP) circuits have proven useful in quantum generative learning models, particularly for binary distributions. However, when applied to non-binary datasets, they exhibit notable limitations: mapping integer values into qubit-compatible binary representations often destroys the original metric structure of the data. In this paper we aim to extend them to a qudits formulation operating on an integer mapping of the data. The IQP quantum circuit is adapted to encode each integer valued pixel into a bit-string of fixed length and quantum gates are transformed to follow the qudit formalism. As a generative machine learning approach, a suitable loss function for the circuit training and the calculation of the covariance matrix among features are developed and validated on the energy deposits from single-particle electron showers in the electromagnetic calorimeter of the CLIC detector. The method proposed in this work can be also extended to other applications that utilize quantum generative machine learning for non-binary data.

quant-ph↗

arXiv2026

Fermion lattices can be simulated by same-size qubit lattices with $\mathcal{O}(1)$ interaction overhead

Local interactions among electrons underlie many complex properties of correlated materials. While the Jordan-Wigner transformation can preserve this locality along one spatial dimension, interactions along the remaining dimensions typically incur substantial overhead. We show how to simulate all geometrically local interactions on an $N$-site two-dimensional fermion lattice with no asymptotic overhead in the number of interactions and no space overhead. The primary overhead of our method is circuit depth, which on a qubit lattice matches that of fermionic swap networks, scaling as $\mathcal{O}(\sqrt{N})$, but reduces to $\mathcal{O}(\log N)$ on reconfigurable qubit arrays and to $\mathcal{O}(1)$ in lattice-surgery-based surface-code architectures. This is enabled by dynamically reorienting the Jordan-Wigner transformation to switch the lattice dimension along which locality is preserved. Furthermore, we study fermion routing, as required for the simulation of non-local interactions. When using qubit lattices, we reach resource scaling that asymptotically matches that of qubit routing, whilst on fully connected qubit devices, a depth scaling arbitrarily close to $\mathcal{O}(\log N)$ is reached. This allows the fermionic fast Fourier transform to be implemented on qubit lattices with asymptotically optimal resource scaling under these locality constraints. Notably, all of our constructions naturally extend to $d$-dimensional lattices. Beyond scaling improvements, we show explicit examples of our method, including Fermi-Hubbard-model simulations of the square-, Lieb- and kagome lattice and the fermionic fast Fourier transform.

quant-ph↗

arXiv2026

Parity-unfolded distillation architecture for noise-biased platforms

We introduce the parity-unfolded architecture, a fault-tolerant quantum computing scheme that relies on direct preparation and teleportation of small-angle rotations $ Z^{1/2^{k}}$ rather than approximating them with the conventional (Clifford + $T$) gate set. The architecture is enabled by efficient distillation of gates from an arbitrary level of the Clifford hierarchy, which we refer to as parity unfolding. With it, a state $|Z_k\rangle = Z^{1/2^{k}}|{+}\rangle$ can be prepared fault-tolerantly using $2^{k+3} + O(2^{k/2})$ biased-noise qubits on a planar chip with nearest-neighbour connectivity. For algorithms requiring native $Z^{1/2^{k}}$ gates, such as the Quantum Fourier Transform and phase estimation, the proposed scheme allows to reduce resource overheads for up to $k=7$, i.e., up to $T^{1/32}$. Furthermore, when used for the synthesis of arbitrary small-angle rotations, parity-unfolded distillation of ($T$ + $\sqrt{T}$) reduces the minimum achievable logical error rate by 43% while cutting the resource requirements by 26%, when compared to unfolded distillation of only the $T$ gate.

quant-ph↗

arXiv2026

Demonstrating Record Fidelity for the Quantum Fourier Transform

We demonstrate the Parity Architecture on quantum hardware, using the quantum Fourier transform (QFT) as a benchmark. As a result, a record performance in both fidelity and qubit count is achieved using quantum processors with a native CZ-based instruction set. On the IBM Heron r3 chip, a process fidelity of the QFT algorithm of ${F \approx 10^{-2}}$ for ${N=50}$ qubits is achieved. The scaling of the speedup compared to previous swap-based methods is super-exponential $\mathcal{O}(\exp(N^2))$. Furthermore, we show that the scaling can be improved further by including iSWAP gates in the instruction set.

quant-ph↗

arXiv2026

YZ-plane measurement-based quantum computation: Universality and Parity Architecture implementation

We define the class of register-logic graphs and prove that any uniformly deterministic measurement-based quantum computation (MBQC) where the inputs coincide with the outputs must be driven on such graphs by measurements in the $YZ$ plane of the Bloch sphere. This observation is revisited in the context that goes beyond uniform determinism, where we present a universal $YZ$-plane-only measurement pattern and establish a connection between $YZ$-plane-only and $XZ$-plane-only patterns. These results conclude the line of research on universal patterns with measurements restricted to one of the principal planes of the Bloch sphere. We further demonstrate, within the framework of the Parity Architecture, that $YZ$-plane patterns with the register-logic graph can be embedded into another graph with purely local interactions, and we extend this case to the scenario of universal quantum computation.

quant-ph↗

arXiv2026

Spin Model for Quantum Annealing with Kerr Parametric Oscillators

Coherent states offer a promising path for near-term quantum computing due to their inherent protection against bit-flip noise. However, their large photon numbers can be challenging for numerical simulation. This paper introduces an effective model, representing coherent-state quantum annealing using spin-1/2 degrees of freedom. We demonstrate that this model yields accurate predictions for realistic experimental settings and can therefore serve as a practical tool for optimizing future quantum hardware.

quant-ph↗

arXiv2025

A physics-informed, plug-and-play dose engine for gradient-based radiotherapy treatment planning

Radiotherapy treatment planning remains a time-intensive iterative process requiring expert intervention in commercial treatment planning system (TPS). While machine learning approaches have demonstrated promise, most remain depedent on TPS-based dose calculation or surrogate dose models, preventing direct optimization of deliverable treatment plan parameters. We propose PyDoseRT (PDRT), a physics-informed, GPU-accelerated dose engine implemented in PyTorch that computes dose distributions directly from treatment delivery parameters (i.e., MLC leaf positions, jaw positions, gantry angles, and monitor units). The engine preserves gradient information throughout the dose computation pipeline, enabling gradient-based optimization of hardware-constrained treatment plans without the reliance on a commercial TPS. PDRT was evaluated on 19 and 162 clinical VMAT prostate cancer plans from two hospitals (with different treatment machines). When recalculating clinical plans, PDRT achieved high 3D gamma pass rates (mean 96.8% for 2%/2 mm and 98.9% for 3%/3 mm, depending on cohort). All optimized plans converged to clinically acceptable solutions and passed deliverability verification when imported into a commercial TPS. This physics-informed framework eliminates TPS dependency for radiotherapy optimization research by enabling gradient-based planning while ensuring that delivery parameters remain in the machine-feasible range. The gradient-enabled dose engine allows exploration of novel optimization strategies and objective functions while maintaining clinical validity. The proposed approach provides a research platform for investigating real-time adaptive radiotherapy concepts, automated planning workflows, and TPS-independent optimization strategies, and democratizing radiotherapy research, by exposing gradient-enabled, hardware-aware, open-source dose computation.

physics.med-ph↗

arXiv2025

Bundling of bipartite entanglement

We investigate bipartite entanglement and prove that in constrained energy subspaces, the entanglement spectra of multiple bipartitions are the same across the whole subspace. We show that in quantum many-body systems the bipartite entanglement entropy is affected in such a way that it forms "bundles" under unitary time evolution. Leveraging the structure of the subspace, we present methods to verify whether the entanglement spectrum of two bipartitions is identical throughout the entire subspace. For the subspace defined by the parity embedding, we further provide an algorithm that can determine this in polynomial time.

quant-ph↗

arXiv2025

Fault-tolerant multi-qubit gates in Parity Codes

We present a set of efficiently implementable logical multi-qubit gates in concatenated quantum error correction codes using parity qubits. In particular, we show how fault-tolerant high-weight rotation gates of arbitrary angle can be implemented on single physical qubits of a classical stabilizer code, or on localized regions of full quantum error correction codes. Similarly, we show how transversal CNOT gates can implement logical parity-controlled-NOT operations between arbitrarily many logical qubits. Both operation types can be implemented and in many cases parallelized without the use of lattice surgery or the need for complicated routing operations.

quant-ph↗

arXiv2025

Expanding the Neutral Atom Gate Set: Native iSWAP and Exchange Gates from Dipolar Rydberg Interactions

We present a native realization of iSWAP and parametrized \textit{exchange} gates for neutral-atom quantum processing units. Our approach leverages strong dipole-dipole interactions between two different dipole-coupled Rydberg states, employing optimal control techniques to design high-fidelity, time-efficient gate pulses. To minimize experimental complexity, we utilize global driving fields acting identically on all atoms and apply pulse smoothing techniques. While detrimental van der Waals interactions pose a significant challenge, we demonstrate that for both $^{133}$Cs, as a representative alkali atom, and $^{88}$Sr, an alkaline-earth species, high-fidelity pulses can nevertheless be obtained over a broad range of parameters. We identify candidate protocols with reduced susceptibility to noise and analyze their performance under realistic conditions, accounting for atomic motion, Rydberg decay, and experimentally motivated laser frequency and intensity noise. Crucially, we demonstrate that in both Alkali and alkaline-earth-based systems, we can obtain fast iSWAP gates with fidelities of $99.9\%$ under realistic experimental conditions. These results pave the way for expanding the neutral-atom gate set beyond conventional Rydberg-blockade-based entangling gates.

quant-ph↗

arXiv2025

Replacement-Type Quantum Gates

We introduce the paradigm of replacement-type quantum gates. This type of gate introduces input qubits, candidate qubits, and output qubits. The candidate qubits are prepared such, that a displacement conditional on the input qubit results in the targeted output state. Finally, the circuit continues with the output qubits constructed from the candidate qubits instead of the input qubits, thus the name "replacement-type gate". We present examples of replacement-type $X$ and $\mathrm{CNOT}$ gates realized with spin qubits and with neutral atom qubits with error rates predicted near the threshold of the XZZX surface code. By making use of the extended Hilbert space, including the position of the particles, these gates approximately preserve the innate noise bias of the qubits. The gate preserves the noise bias which motivates advanced quantum computer architectures with quantum error correction.

quant-ph↗

arXiv2025

Multi-Qubit Parity Gates for Rydberg Atoms in Various Configurations

We present a native approach for realizing multi-qubit parity phase gates in neutral atom systems through global phase modulation of a Rydberg excitation laser. By shaping the temporal profile of the laser's phase, we enable high fidelity, time efficient entangling operations between multiple qubits without requiring individual qubit addressing. To mitigate intrinsic noise sources including spontaneous decay and motional effects, we develop a noise-aware optimal control framework that reduces gate errors under the presence of noise while maintaining smooth pulse profiles suitable for experimental implementation. In addition to equidistant qubit arrangements, we explore the impact of non-equidistant atomic configurations, where interaction inhomogeneity becomes significant. In these cases, the flexibility of our control approach helps to compensate for such variations, supporting reliable gate performance across different spatial layouts. These results facilitate the practical implementation of complex, multi-qubit quantum operations in near-term neutral atom quantum processors.

quant-ph↗

arXiv2025

The Parity Flow Formalism: Tracking Quantum Information Throughout Computation

We propose the Parity Flow formalism, a method for tracking the information flow in quantum circuits. This method adds labels to quantum circuit diagrams such that the action of Clifford gates can be understood as a recoding of quantum information. The action of non-Clifford gates in the encoded space can be directly deduced from those labels without backtracking. An application of flow tracking is to design resource-efficient quantum circuits by changing any present encoding via a simple set of rules. Finally, the Parity Flow formalism can be used in combination with stabilizer codes to further reduce quantum circuit depth and to reveal additional operations that can be implemented in parallel.

quant-ph↗

arXiv2025

Optimal Decoder for the Error Correcting Parity Code

We present a two-step decoder for the parity code and evaluate its performance in code-capacity and faulty-measurement settings. For noiseless measurements, we find that the decoding problem can be reduced to a series of repetition codes while yielding near-optimal decoding for intermediate code sizes and achieving optimality in the limit of large codes. In the regime of unreliable measurements, the decoder demonstrates fault-tolerant thresholds above 5% at the cost of decoding a series of independent repetition codes in (1 + 1) dimensions. Such high thresholds, in conjunction with a practical decoder, efficient long-range logical gates, and suitability for planar implementation, position the parity architecture as a promising candidate for demonstrating quantum advantage on qubit platforms with strong noise bias.

quant-ph↗