arXiv subjects

Michal Hajdušek

Publications and source records attributed to Michal Hajdušek.

At least 19 recordsLinked to original sources

arXiv2026

Cross-Validation of Open-Source Quantum Network Simulators

We present a comparative analysis of two open-source quantum network simulators, QuISP and SeQUeNCe, focusing on cross-validation of basic networking tasks to ensure consistency and accuracy in simulation outputs. Although both simulators are designed to study quantum network management policies and their dynamics under complex noise models, their differing underlying assumptions can lead to variations in simulation results. We highlight the discrepancies in how the two simulators handle connections, internal network node processing time, and classical communication, resulting in significant quantitative and qualitative differences in the time required to perform basic network tasks such as entanglement generation, purification, and swapping. We simulate common scenarios between the simulators to compare both the latency of resource distribution and the fidelity of the distributed resources. Our findings indicate that while the simulators differ in the time required to complete network tasks---a constant factor difference attributable to their respective connection models---they agree on the fidelity of the distributed resources under identical error parameters. This work demonstrates a crucial first step towards enhancing the reliability and reproducibility of quantum network simulations, as well as leading to full protocol development. Furthermore, our benchmarking methodology establishes a foundational set of tasks for the cross-validation of simulators to study future quantum networks.

quant-ph↗

arXiv2026

Topology-Dependent Enhancement of Entanglement Extraction in Repeater Graph States

Quantum repeaters are essential for establishing long-distance quantum communication to overcome the exponential decay of entanglement due to photon loss. Traditional repeater architectures rely on physical quantum memory, which introduces decoherence and poses significant practical implementation challenges. The repeater graph state (RGS) architecture offers a promising memory-less alternative that is inherently resilient to photon losses. A key challenge in implementing RGS lies in the requirement for highly efficient graph state generators and complex qubit measurement. In this work, we aim to investigate the strategies for extracting the maximum number of Bell pairs from the RGS structure via its qubit connection to resolve the well-known bottleneck problem of RGS in which only a single Bell pair can be extracted from a complete bipartite graph state. From simulations, we observe that the maximum number of extracted Bell pairs depends on its connection topology, where the Bell-pair yield tends to be maximal at low to moderate edge densities. As the number of network hops increases, the RGS must be equipped with higher inner-qubit connectivity to maintain a sufficient yield of extractable Bell pairs. Thus, the expected resource requirement shifts toward the use of RGSs with higher inner-qubit connectivity.

quant-ph↗

arXiv2026

Promise and Challenges of Distimation

Estimating the quality of raw entangled states and distilling high-fidelity entanglement traditionally require two separate link-layer protocols in a quantum network stack, each consuming its own share of fragile entangled pairs. The recently introduced distimation concept merges these two protocols by directly extracting state estimation data from the classical syndromes generated during entanglement distillation. By removing the dedicated "test-then-distill'' stage, distimation lowers the number of raw entangled pairs required to operate the network, reduces latency, and streamlines the network control plane. The paradigm is especially attractive for near-term hardware platforms, where entanglement generation remains a severe bottleneck. Alongside these promises, distimation introduces new engineering challenges, ranging from accurate local-device modeling to protocols for tracking time-varying sources. This article surveys the core principles of distimation, quantifies expected gains for realistic architectures, and outlines a research roadmap toward making distimation a standard building block in future quantum networks.

quant-ph↗

arXiv2026

Quantum Synchronization

Natural and engineered classical systems are replete with examples of synchronization, understood as the adjustment of rhythms of physical systems. Such synchronization is at the heart of the stability of several classical technologies, such as mechanical bridges and electrical networks. Given the advent of quantum simulation and computation technologies, it is natural to study a quantum analogue of synchronization and explore novel applications. This review surveys synchronization in few and many-body quantum systems, measures that quantify them, and their applications to quantum technologies.

quant-ph↗

arXiv2026

Structure-Informed Multiple Sequence Alignment: A Formal Model and Hardness Results

We formulate a structure-informed multiple sequence alignment problem, denoted MSA-S. The model abstracts biological sequences as strings and structural information as designated position-pairs. It augments a fixed pairwise string score, defined by a fixed non-gap symbol-pair scoring rule and fixed affine gap penalties, with a binary overlap score on designated position-pairs, which can be interpreted as a contact-map overlap score in structural applications. This yields a fixed-score, integer-valued optimization model suitable for complexity-theoretic analysis. Under this formulation, we show that the decision problem MSA-S-DEC is NP-complete for a broad class of fixed pairwise string scoring schemes. We also show that NP-hardness persists even under the restriction that every designated position-pair set is nonempty and the pair-overlap threshold is strictly positive. For the associated scalarized optimization problem MSA-S-OPT(lambda) with any fixed rational constant lambda >= 1, we further show that, under the canonical unit scheme for the non-gap symbol-pair scoring rule, MSA-S-OPT(lambda) admits no polynomial-time approximation scheme (PTAS) even for two input strings (k = 2), unless P = NP. These results establish a formal complexity-theoretic baseline for structure-informed multiple sequence alignment.

cs.CC↗

arXiv2026

Space-Time Tradeoffs of Pauli-Based Computation in Distributed qLDPC Architectures

Pauli-based computation (PBC) provides a universal framework for executing fault-tolerant quantum algorithms using Pauli measurements and magic states. In monolithic architectures, the serialized nature of PBC directly ties runtime to a circuit's T-gate count, making it slow on metrics like circuit depth. However, in distributed quantum computing (DQC), the primary bottleneck is remote Bell pair generation. We investigate the tradeoff between error-correcting code block size and execution time of PBC within the Q-Fly architecture at intermediate scale, limiting individual node capacities to reflect near-term constraints while supplying abundant network nodes to minimize routing and compilation effects. We find that large qLDPC code blocks outperform the surface code baseline in terms of execution time by up to an order of magnitude when evaluated against quantum optimization algorithms. By moving groups of qubits to free nodes to bypass the sequential bottleneck of PBC, the large-block architecture minimizes network operations and achieves faster overall execution. This demonstrates that PBC is a competitive model in the distributed regime, establishing it as a practical compilation baseline for qLDPC systems before invoking more efficient transversal or homological gates.

quant-ph↗

arXiv2026

Architecture and protocols for all-photonic quantum repeaters

The all-photonic quantum repeater scheme, utilizing a type of graph state called the repeater graph state (RGS), promises resilience to photon losses and operational errors, offering a fast Bell pair generation rate limited only by the RGS creation time (rather than enforced round-trip waits). While existing research has predominantly focused on RGS generation and secret key sharing rate analysis, there is a need to extend investigations to encompass broader applications, such as distributed computation and teleportation, the main tasks envisioned for the Quantum Internet. Here we propose a new emitter-photonic qubit building block and an RGS protocol that addresses several key considerations: end node involvement in connection establishment, decoding of logical qubits within the RGS, and computing the Pauli frame corrections at each participating node to ensure the desired correct end-to-end Bell pair state. Our proposed building block significantly reduces the total number of emissive quantum memories required for end nodes and seamlessly integrates all-photonic and memory-based repeaters under the same communication protocol. We also present an algorithm for decoding logical measurement results, employing graphical reasoning based on graph state manipulation rules.

quant-ph↗

arXiv2026

Quantum Hamlets: Distributed Compilation of Large Algorithmic Graph States

We investigate the problem of compiling the generation of graph states to arbitrarily many distributed homogeneous quantum processing units (QPUs), providing a scalable partitioning algorithm and graph state generation protocol to minimize the number of Bell pairs required. Current approaches focus on the naive metric of cut edges to estimate the quantum communication cost. We show that the problem of balanced k graph partitioning, with the objective of minimizing the sizes of the maximum matchings between the partitions, leads to lower entanglement requirements across partitions. Our heuristic algorithm, BURY, partitions graph states to require fewer Bell pairs for generation than state-of-the-art k partition algorithms. Furthermore, we show that BURY reduces the cut-rank of the partitions, demonstrating that the partitioning found by our algorithm is likely to minimize the Bell pair utilization of any future improved distributed graph state generation protocol. We also discuss how our methods apply to the dynamic case where the graph state generation and measurement are performed concurrently. Our compilation approach provides a scalable foundation for reducing quantum network overhead for distributed measurement-based quantum computation (MBQC), as well as any scheme where distributed graph state generation is desired.

quant-ph↗

arXiv2026

Optimizing Resource Allocation in a Distributed Quantum Computing Cloud: A Game-Theoretic Approach

Quantum cloud computing is essential for achieving quantum supremacy by utilizing multiple quantum computers connected via an entangling network to deliver high performance for practical applications that require extensive computational resources. With such a platform, various clients can execute their quantum jobs (quantum circuits) without needing to manage the quantum hardware and pay based on resource usage. Hence, defining optimal quantum resource allocation is necessary to avoid overcharging clients and to allow quantum cloud providers to maximize resource utilization. Prior work has mainly focused on minimizing communication delays between nodes using multi-objective techniques. Our approach involves analyzing the problem from a game theory perspective. We propose a quantum circuit partitioning resource allocation game model (QC-PRAGM) that minimizes client costs while maximizing resource utilization in quantum cloud environments. We extend QC-PRAGM to QC-PRAGM++ to maximize local gates in a partition by selecting the best combinations of qubits, thereby minimizing both cost and inter-node communication. We demonstrate analytically that clients are charged appropriately (with a total cost at most $\frac{4}{3}$ the optimal cost) while optimizing quantum cloud resources. Further, our simulations indicate that our solutions perform better than traditional ones in terms of the cost per quantum node, total cost, maximum cost, number of partitions, and number of remote gates.

quant-ph↗

arXiv2026

A Tailored Fidelity Estimation and Purification Method for Entangled Quantum Networks

We present a method to conduct both quantum state reconstruction and entanglement purification simultaneously that is advantageous in several respects over previous work in this direction, showing that the number of Bell pairs necessary to boot a quantum network can be significantly reduced compared to an existing method. The existing method requires at least $10^5$ Bell pairs for the state reconstruction phase to estimate that the state is of fidelity $0.99$ within the error range of $10^{-2}$, whereas our approach only requires around $2,841$ to be certain with $99.7\%$ of confidence that the estimated fidelity lies within $[0.99-0.01, 0.99+0.01]$. In addition, in our approach we can start with a lower fidelity Bell pair and purify it multiple times, estimating at the same time the resultant fidelity with guarantee of $99.7\%$ that the fidelity estimate lies within a certain range. Moreover, the existing method cannot correct both bit-flip and phase-flip errors at the same time and can only correct one of these, whereas our approach can correct both bit-flip and phase-flip errors simultaneously. This research produces numerical estimates for the number of Bell pairs actually needed to guarantee a certain threshold fidelity $F$. The research can support the functioning real-world quantum networking by providing the information of the time needed for the bootstrapping of a quantum network to finish.

quant-ph↗

arXiv2026

Determining Molecular Ground State with Quantum Imaginary Time Evolution using Broken-Symmetry Wave Function

The Hartree-Fock (HF) wave function, commonly used for approximating molecular ground states, becomes nonideal in open shell systems due to the inherent multi-configurational nature of the wave function, limiting accuracy in Quantum Imaginary Time Evolution (QITE). We propose replacing the HF wave function with a spin- and spatial-symmetry broken wave function, enhancing convergence by adding a spin operator, $S^2$ as a penalty term to the original molecular Hamiltonian. We verify that this approach provides good convergence behavior towards the lowest energy eigenstate using direct matrix exponentiation for Imaginary Time Evolution (ITE). Numerical simulations were performed on the hydrogen molecule and a square tetrahydrogen cluster using measurement-assisted unitary approximation in QITE. QITE demonstrates faster convergence to the ground state with broken symmetry (BS) compared to HF, particularly after the molecule exhibits a diradical character of 0.56 for hydrogen. Prior to this point, HF remains more effective, suggesting a transition threshold of diradical character for wave function selection. Additionally, the overlap analysis with Complete Active Space Configuration Interaction (CAS-CI) wave function shows that BS has a larger initial overlap than HF in higher-spin, multi-configurational systems like triple bond dissociation in nitrogen molecule. This method provides a pathway for improved energy simulations in open shell systems, where wave function accuracy significantly impacts downstream quantum algorithms and practical applications in quantum chemistry.

physics.chem-ph↗

arXiv2025

Q-Fly: An Optical Interconnect for Modular Quantum Computers

Much like classical supercomputers, scaling up quantum computers requires an optical interconnect. However, signal attenuation leads to irreversible qubit loss, making quantum interconnect design guidelines and metrics different from conventional computing. Inspired by the classical Dragonfly topology, we propose a multi-group structure where the group switch routes photons emitted by computational end nodes to the group's shared pool of Bell state analyzers (which conduct the entanglement swapping that creates end-to-end entanglement) or across a low-diameter path to another group. We present a full-stack analysis of system performance, a combination of distributed and centralized protocols, and a resource scheduler that plans qubit placement and communications for large-scale, fault-tolerant systems. We implement a prototype three-node switched interconnect to justify hardware-side scalability and to expose low-level architectural challenges. We create two-hop entanglement with fidelities of 0.6-0.76. Our design emphasizes reducing network hops and optical components to simplify system stabilization while flexibly adjusting optical path lengths. Based on evaluated loss and infidelity budgets, we find that moderate-radix switches enable systems meeting expected near-term needs, and large systems are feasible. Our design is expected to be effective for a variety of quantum computing technologies, including ion traps and neutral atoms.

quant-ph↗

arXiv2025

Efficient graph-diagonal characterization of noisy states distributed over quantum networks via Bell sampling

Graph states are an important class of entangled states that serve as a key resource for distributed information processing and communication in quantum networks. In this work, we propose a protocol that utilizes a Bell sampling subroutine to characterize the diagonal elements in the graph basis of noisy graph states distributed across a network. Our approach offers significant advantages over direct diagonal estimation using unentangled single-qubit measurements in terms of scalability. Specifically, we prove that estimating the full vector of diagonal elements requires a sample complexity that scales linearly with the number of qubits ($\mathcal{O}(n)$), providing an exponential reduction in resource overhead compared to the best known $\mathcal{O}(2^n)$ scaling of direct estimation. Furthermore, we demonstrate that global properties, such as state fidelity, can be estimated with a sample complexity independent of the network size. Finally, we present numerical results indicating that the estimation in practice is more efficient than the derived theoretical bounds. Our work thus establishes a promising technique for efficiently estimating noisy graph states in large networks under realistic experimental conditions.

quant-ph↗

arXiv2025

Probabilistic Graybox Characterization of Quantum Devices with Bayesian Neural Networks

While the Graybox characterization method allows for implicit noise models and is platform-agnostic, the method lacks uncertainty quantification. Characterization of quantum devices is a crucial process that enables researchers to gain insight from experimental settings. Graybox characterization combines known system dynamics with unknown transformations, where the latter is modeled using machine learning. Prediction uncertainty helps researchers make informed decisions. It allows valuable insights from the devices without overconfidence. We therefore develop a probabilistic Graybox characterization model using probabilistic machine learning, specifically Bayesian Neural Networks, and utilize binary measurement outcomes directly for inference. With stochastic noise in a quantum device, we analyze statistical properties of the measurement data. Our results show that the model's prediction performance solely depends on its ability to capture the expected value of the true expectation value. Our proposed probabilistic Graybox model outperforms the original model by up to 1.9 times in capturing the distribution of observed data. We expect that our results will serve as an additional tool for characterizing quantum devices with uncertainty estimation, as they provide a flexible choice that can be utilized even without extensive prior knowledge of the noise model of the devices.

quant-ph↗

arXiv2025

Quantum Circuit Design for Decoded Quantum Interferometry

Decoded Quantum Interferometry (DQI) is a recently proposed quantum algorithm for approximating solutions to combinatorial optimization problems by reducing instances of linear satisfiability to bounded-distance decoding over superpositions of quantum states. A central challenge in realizing DQI is the design of a decoder that operates coherently on quantum superpositions. In this work, we present a concrete quantum circuit implementation of DQI, with a focus on the decoding subroutine. Our design leverages a reversible Gauss-Jordan elimination circuit for the decoding stage. We analyze the circuit's depth and gate complexity and validate its performance through simulations on systems with up to 30 qubits. These results establish a concrete foundation for scalable implementations of DQI and open the door to future algorithmic refinements and hardware-level realizations.

quant-ph↗

arXiv2025

Graybox characterization and calibration with finite-shot estimation on superconducting-qubit experiments

Characterization and calibration of quantum devices are necessary steps to achieve fault-tolerant quantum computing. As quantum devices become more sophisticated, it is increasingly essential to rely not only on physics-based models, but also on predictive models with open-loop optimization. Therefore, we choose the Graybox approach, which is composed of an explicit (whitebox) model describing the known dynamics and an implicit (blackbox) model describing the noisy dynamics in the form of a deep neural network, to characterize and calibrate superconducting-qubit devices. By sending a set of selected pulses to the devices and measuring Pauli expectation values, the Graybox approach can train the implicit model and optimize gates based on specified loss functions. We also benchmark our optimized gates on the devices and cross-testing predictive models with two types of loss functions, i.e., the mean squared errors (MSE) of expectation values and the absolute errors (AE) of average gate fidelities (AGF). While the Graybox method allows for flexibility of the implicit noise model, its construction relies on a finite measurement shots dataset. We thus apply the decomposition of expected MSE loss to show that the finite-shot estimation of expectation values is the main contribution to the minimum value achievable of the expected MSE loss. We also show that the expected loss is an upper bound of the expected absolute error of AGF between the exact value and model prediction. Our results provide insights for quantum device characterization and gate optimization in experiments where only finite shots of data are available.

quant-ph↗

arXiv2025

A double selection entanglement distillation-based state estimator

With the advent of practical quantum communication networks drawing closer, there is a growing need for reliable estimation protocols that can efficiently characterize quantum resources with minimum resource overhead requirement. A novel approach to this problem is to integrate an estimator into an existing network task, thereby removing the need for an additional characterization protocol. In this work, we show that the measurement statistics of a double selection distillation protocol alone can be used to efficiently estimate the Bell-diagonal parameters of the undistilled states, as well as the resulting distilled states after additional post-processing. We also demonstrate that this novel estimator outperforms the previously proposed distillation-based estimator in terms of resource complexity.

quant-ph↗

arXiv2025

Integrating Entanglement Purification into All-Photonic Quantum Repeaters

We propose a purification-enhanced all-photonic quantum repeater scheme based on repeater graph states (RGS) framework that leverages the recently proposed half-RGS building block. This framework addresses a longstanding open question--how to naturally integrate entanglement purification with an all-photonic scheme--by enabling long-distance purification without disrupting the core design. Our framework utilizes optimistic purification performed directly on the half-RGS primitives across long distances without waiting for heralding outcomes. The overhead is modest: the RGS generation slows down proportionally with the number of purification rounds, and each round requires only one additional quantum emitter per half-RGS source. However, since the generation time is negligible compared to the end-to-end communication delay, the total latency remains effectively dominated by communication time, similar to frameworks without purification. Our framework enables flexible purification scheduling along the connection path, making it compatible with memory-based strategies, a rich body of research on purification scheduling and optimization that was previously thought inapplicable to the RGS scheme. Through numerical evaluation, we compare the performance of our framework with purification between memories at end nodes.

quant-ph↗