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arxiv: 2509.04029 · v2 · pith:F4EEHPFMnew · submitted 2025-09-04 · 🪐 quant-ph

A Framework for Quantum Data Center Emulation Using Digital Quantum Computers

Seyed Navid Elyasi , Paolo Monti , Jun Li , Rui Lin This is my paper

Pith reviewed 2026-05-18 19:18 UTC · model grok-4.3

classification 🪐 quant-ph
keywords quantum data centerdistributed quantum computinghardware emulationqubit partitioninginterconnect noiseancilla qubit modelremote gatesGrover search
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The pith

Partitioning one quantum processor's qubit map into logical QPUs lets existing hardware emulate a quantum data center with tunable interconnect noise.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper sets out a way to test distributed quantum computing by splitting the physical couplings on a single chip into separate logical processors. Noise from real-world links such as transduction loss and fiber attenuation is introduced through extra ancilla qubits whose collisions with the signal qubits produce controllable error channels. These channels are then realized as ordinary gates, so the whole emulation runs directly on current digital quantum hardware. Because the method stays inside the physical device, it sidesteps the exponential memory wall of classical simulators while still capturing hardware-level noise and timing. The authors verify the approach by running remote gates, a distributed Grover search, and larger circuits such as Grover and the quantum Fourier transform, all with usable fidelity across the virtual QPUs.

Core claim

By dividing a single processor's coupling map into multiple logical QPUs and inserting ancilla qubits whose collisional dynamics reproduce transduction and optical-fiber loss, the resulting gate circuit turns the inter-QPU links into adjustable noisy quantum channels that can be executed on present-day digital hardware.

What carries the argument

Ancilla-qubit model derived from quantum collisional dynamics, which is compiled into gate-based noisy communication channels between partitioned regions of the coupling map.

If this is right

  • Remote two-qubit gates between logical QPUs can be run with user-controlled noise levels on existing superconducting hardware.
  • Distributed Grover search implementations previously shown on ion traps can be reproduced on superconducting processors.
  • Larger algorithms such as Grover search and the quantum Fourier transform maintain reasonable output fidelity when executed across the emulated QPUs.
  • The platform scales beyond classical simulation limits because all noise and timing are realized by physical qubits rather than by state-vector multiplication.
  • Any quantum platform that supports the Qiskit SDK can host the same emulation without new hardware.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Different QDC topologies could be explored simply by changing how the coupling map is partitioned and how the ancilla noise parameters are set.
  • The same technique might be used to benchmark candidate interconnect technologies before they are built into a real multi-chip system.
  • As qubit counts grow, the emulation could serve as a rapid prototyping layer for software stacks that schedule work across many logical QPUs.

Load-bearing premise

The ancilla-qubit collisions derived from quantum collisional dynamics accurately reproduce the noise that real transduction and fiber links would introduce between separate QPUs.

What would settle it

Execute the same distributed circuit on a physical multi-QPU testbed with measured interconnect loss and compare the observed fidelity and error rates to those obtained from the single-chip emulation.

Figures

Figures reproduced from arXiv: 2509.04029 by Jun Li, Paolo Monti, Rui Lin, Seyed Navid Elyasi.

Figure 1
Figure 1. Figure 1: A visual illustration of the core concept: a single quantum chip emulates a network of interconnected QPUs. The chip’s coupling map is partitioned into multiple qubit groups, with existing couplings between groups interpreted as virtual interconnects between the emulated QPUs. (QPUs) are interconnected to function as a single distributed system [4], [5]. QDCs are being explored for a range of potential app… view at source ↗
Figure 2
Figure 2. Figure 2: (a) Interconnected QPUs in a QDC, (b) non-local oper￾ations between interconnected QPUs, where CU stands for a ontrol unitary gate. implement our emulation approach in Section II-C. Section III presents the emulation results, including various RG protocols and the cross-QPU entanglement of processing qubits in Section III-A and Section III-B. We then extend the analysis to more complex scenarios by demonst… view at source ↗
Figure 3
Figure 3. Figure 3: (a) A representation of a quantum system (S) inter￾acting with its surrounding environment (E), where information leakage occurs continuously. (b) A schematic depiction of the CM, where the environment is discretized into smaller, independent seg￾ments E1, E2, . . . , En, each interacting with the system sequentially through corresponding unitary evolution operators Uˆ1,Uˆ2, . . . ,Uˆn. both stochastic sim… view at source ↗
Figure 4
Figure 4. Figure 4: (a) a visual representation of the proposed scenario for simulating noisy entanglement within a quantum QDC, where QPUs are interconnected using a mesh topology; (b) a zoomed-in view of a selected section from (a), highlighting the communication setup; (c) a discretized noise model used to capture the imperfections in the communication channel between QPUs. A significant benefit of CM is that its unitary-b… view at source ↗
Figure 5
Figure 5. Figure 5: The provided graph illustrates the mapping of fiber discretization steps as described in the system. efficiency compared to optical fiber transmission, we as￾sign a stronger coupling constant to transducer-induced noise κTransducer than to optical fiber noise κFiber, reflecting current technological limitations. For our emulations, we consider widely used telecom fiber types such as G-652-D, G-654-D, and G… view at source ↗
Figure 6
Figure 6. Figure 6: Implementation of a remote CNOT gate using con￾trollable noisy entanglement: (a) Noisy Cat-State Communication (Cat-Comm)-based remote CNOT gate; (b) Noisy teleportation-based remote CNOT gate. With the system model explained and established, the fol￾lowing section focuses on implementing remote quantum gates using our simulation framework on actual quantum hardware, allowing us to assess the practical eff… view at source ↗
Figure 7
Figure 7. Figure 7: Execution of remote CNOT gates: (a) and (b) show the execution of a remote CNOT gate using the cat-comm protocol with the control qubit initialized in states |0⟩ and |1⟩, respectively. (c) and (d) illustrate the execution of a remote CNOT gate using the teleportation￾based protocol, with the control qubit of QPU A prepared in states |0⟩ and |1⟩, respectively [PITH_FULL_IMAGE:figures/full_fig_p006_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Comparison of Bell state generation in monolithic and distributed configurations using a remote CNOT gate over three types of optical fibers. Fig.7(c) and (d), corresponding to control states |0⟩ and |1⟩, respectively. B. Cross-QPU Entanglement of Processing Qubits As a practical demonstration of our proposed frameworks, we generate a Bell state between arbitrary processing qubits located on separate QPUs.… view at source ↗
Figure 9
Figure 9. Figure 9: The cross-QPU entanglement of processing qubits q A 1 from QPU A and q B 4 from QPU B. Section (A) shows the establishment of entanglement along with the introduction of noise to emulate environmental effects. Section (B) applies a Hadamard gate to q A 1 . Section (C) prepares the system for the remote CNOT gate, and finally, Section (D) completes the execution of the remote CNOT gate on q B 4 . the follow… view at source ↗
Figure 11
Figure 11. Figure 11: Comparison of a two-qubit Grover’s search algorithm in both monolithic and distributed configurations for the set of marked states {00, 11, 01, 10}. The initial step of the distributed implemen￾tation is approximately aligned with the experimental results reported in [32]. operator is sufficient to maximize the probability of measuring the correct result. This setup is illustrated in [PITH_FULL_IMAGE:fig… view at source ↗
Figure 12
Figure 12. Figure 12: Execution of the QFT algorithm: (a) Monolithic implementation of the 5-qubit QFT; (b) Reconfigured monolithic version optimized to reduce SWAP gates (It must be decomposed into three remote CNOT gates and multiple local gates, which significantly increases the overall error rate); (c) Distributed implementation of the 5-qubit QFT across two interconnected QPUs. and the experimental data reported for ion-t… view at source ↗
Figure 13
Figure 13. Figure 13: The provided graph illustrates the execution of the 5- qubit QFT algorithm in both monolithic and distributed forms. In the distributed form, which is indexed as ”1 to 10” on the x-axis, and in the monolithic form, indexed as ”mono”. IV. CONCLUSION In this work, we introduce and demonstrate framework for emulating QDCs on digital quantum computing hardware. By logically partitioning a single superconducti… view at source ↗
read the original abstract

As quantum computers scale, single-chip architectures face inherent limitations in qubit count. It drives the need for modular quantum computing and Quantum Data Centers (QDCs), where multiple quantum processor units (QPUs) are interconnected to enable the distributed execution of a quantum algorithm. However, evaluating distributed quantum computing (DQC) architectures is challenging. Classical simulation is limited by the growth of exponential state vector, limiting their ability to model large systems and realistically capture hardware noise and timing. Meanwhile, implementing QDC introduces interconnect noise challenges such as transduction inefficiency and optical fiber losses. In this work, we introduce a hardware-based emulation framework by partitioning a single quantum processor's qubit coupling map into multiple logical QPUs. We show how noise arising from transduction and optical fiber can be modeled by adding an ancilla qubit representing the environment based on quantum collisional dynamics. This model is then translated into a gate-based circuit, in which the couplings between each portion act as controllable noisy quantum communication channels. We demonstrate the framework on IBM quantum hardware by executing remote gates under controllable communication noise. To highlight the flexibility of the platform, we further replicate the implementation results of distributed Grover's search on an ion-trap system. Finally, we test a larger circuit, i.e., Grover's search algorithm and the Quantum Fourier Transform (QFT), achieving reasonable fidelity across logical QPUs. Overall, the framework enables hardware-level emulation beyond the limits of classical scaling, captures noise sources through physical qubits, and is compatible with any platform supporting the Qiskit SDK.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 3 minor

Summary. The paper introduces a hardware-based emulation framework for Quantum Data Centers by partitioning a single quantum processor's qubit coupling map into multiple logical QPUs. Noise from transduction inefficiency and optical fiber losses is modeled by adding an ancilla qubit representing the environment based on quantum collisional dynamics; this is translated into a gate-based circuit where inter-portion couplings act as controllable noisy quantum communication channels. Demonstrations on IBM hardware include remote gates under tunable communication noise, replication of distributed Grover's search from an ion-trap system, and execution of Grover's search and QFT circuits, all reporting reasonable fidelity across logical QPUs.

Significance. If the ancilla-based collisional model is quantitatively validated against realistic optical-link parameters, the framework would offer a practical route to hardware-level testing of distributed quantum algorithms at scales inaccessible to classical simulation, while naturally incorporating device noise through physical qubits. The IBM demonstrations and successful replication of prior ion-trap results provide concrete evidence of platform flexibility and Qiskit compatibility, strengthening the case for its utility in QDC architecture exploration.

major comments (2)
  1. [Abstract / Noise Modeling] Abstract and noise-modeling description: the claim that the ancilla qubit derived from quantum collisional dynamics accurately represents real interconnect noise (transduction inefficiency and optical-fiber losses) lacks quantitative validation against expected loss rates or Kraus operators for realistic optical links. This is load-bearing for the central emulation claim, because the reported 'reasonable fidelity' for remote gates and distributed algorithms cannot be interpreted as faithful reproduction of physical QDC conditions without such a benchmark.
  2. [Demonstration Results] Results for Grover's search and QFT: while 'reasonable fidelity across logical QPUs' is stated, no error bars, full baseline comparisons, or explicit data-exclusion criteria are supplied. This weakens the ability to judge whether the observed performance genuinely demonstrates the framework's advantage over classical simulation limits.
minor comments (3)
  1. The abstract would be strengthened by replacing the qualitative phrase 'reasonable fidelity' with specific numerical values and uncertainties.
  2. Notation for the effective communication channels (e.g., how the ancilla interaction strength maps to gate parameters) should be defined more explicitly to aid reproducibility.
  3. A brief discussion of the computational overhead introduced by the ancilla qubits relative to the logical QPUs would help readers assess scalability.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed comments. We address each major comment below, indicating where revisions will be made to improve the manuscript.

read point-by-point responses

  1. Referee: [Abstract / Noise Modeling] Abstract and noise-modeling description: the claim that the ancilla qubit derived from quantum collisional dynamics accurately represents real interconnect noise (transduction inefficiency and optical-fiber losses) lacks quantitative validation against expected loss rates or Kraus operators for realistic optical links. This is load-bearing for the central emulation claim, because the reported 'reasonable fidelity' for remote gates and distributed algorithms cannot be interpreted as faithful reproduction of physical QDC conditions without such a benchmark.

    Authors: We agree that a more explicit quantitative connection between the tunable ancilla coupling and realistic optical-link parameters would strengthen the central claim. The collisional-dynamics model supplies a physically motivated, gate-based channel whose noise strength is controlled by a single parameter; this parameter can in principle be matched to measured loss rates or to the Kraus operators of amplitude-damping channels that approximate fiber and transduction loss. In the revised manuscript we will add a short subsection that (i) relates the effective channel fidelity to typical fiber-loss values (e.g., 0.2 dB km⁻¹) and transduction efficiencies reported in the literature, and (ii) shows the corresponding Kraus representation for a representative loss level. These additions will allow readers to interpret the reported fidelities in the context of physical QDC conditions while preserving the framework’s platform-agnostic character. revision: yes

  2. Referee: [Demonstration Results] Results for Grover's search and QFT: while 'reasonable fidelity across logical QPUs' is stated, no error bars, full baseline comparisons, or explicit data-exclusion criteria are supplied. This weakens the ability to judge whether the observed performance genuinely demonstrates the framework's advantage over classical simulation limits.

    Authors: We concur that the presentation of the experimental results would benefit from greater statistical rigor. In the revised version we will (i) report all fidelities with statistical error bars obtained from repeated circuit executions on the IBM hardware, (ii) include direct comparisons to ideal (noiseless) simulations and to runs performed without the tunable communication-noise model, and (iii) state the data-exclusion criteria (e.g., rejection of shots from calibrations below a stated threshold or circuits exceeding a maximum depth). These changes will make the performance claims more transparent and will better illustrate the framework’s utility for systems that exceed classical simulation limits. revision: yes

Circularity Check

0 steps flagged

No circularity: hardware emulation framework is empirically self-contained

full rationale

The paper introduces a partitioning-based emulation on real quantum hardware, models interconnect noise by adding ancilla qubits drawn from standard quantum collisional dynamics, and translates the model into executable circuits whose performance is measured directly on IBM devices and ion-trap replications. Reported fidelities for remote gates, distributed Grover, and QFT are empirical outcomes of hardware runs rather than quantities derived from fitted parameters or self-referential equations. No load-bearing step reduces by construction to the paper's own inputs, and the framework relies on platform-independent Qiskit execution plus externally observable noise channels, rendering the derivation self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 1 invented entities

The framework depends on standard quantum mechanics for noise modeling and introduces an ancilla-based representation; no extensive free parameters are detailed in the abstract.

free parameters (1)
  • communication noise strength parameters
    Used to control the modeled noisy quantum channels between logical QPUs.
axioms (1)
  • domain assumption Quantum collisional dynamics can be used to model environment interactions for interconnect noise
    Invoked to justify the ancilla qubit addition for representing transduction and fiber losses.
invented entities (1)
  • ancilla qubit representing the environment no independent evidence
    purpose: To physically model noise in quantum communication channels between logical QPUs
    Newly added to the circuit to emulate real interconnect effects.

pith-pipeline@v0.9.0 · 5809 in / 1547 out tokens · 57077 ms · 2026-05-18T19:18:19.104478+00:00 · methodology

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Reference graph

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