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arxiv: 2606.32030 · v1 · pith:S5VBFWXLnew · submitted 2026-06-30 · 🪐 quant-ph

Simulation of Two-qubit Gate Variability and Fidelity of Spin Qubits Built on Nanosheet Technology

Trung Nguyen , Sarah Dweik , Hiu Yung Wong This is my paper

Pith reviewed 2026-07-01 04:52 UTC · model grok-4.3

classification 🪐 quant-ph
keywords silicon spin qubitsnanosheet technologytwo-qubit gatesgate fidelityexchange interactionbias variationscharge noise
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The pith

Millivolt-level bias variations at plunger and middle barrier gates can reduce two-qubit gate fidelity below 99% in nanosheet silicon spin qubits.

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

The paper models silicon spin-qubit double quantum dots on nanosheet technology with three-dimensional Poisson and Schrödinger solvers plus a many-body solver to obtain exchange interactions. It then solves the master equation to quantify how small voltage changes affect two-qubit gate performance. The central finding is that millivolt-scale shifts at the plunger and middle barrier gates push fidelity below the 99% level targeted by many fault-tolerant schemes, while 1/f charge noise is also tracked through its effect on coherence time. A reader would care because silicon spin qubits are meant to ride existing semiconductor lines, yet two-qubit gate quality remains the main scaling bottleneck.

Core claim

Simulations of silicon spin-qubit double quantum dots built on nanosheet technology show that millivolt-level bias variations at the plunger and middle barrier gates reduce the two-qubit gate fidelity below 99%, a common threshold for fault-tolerant quantum-computing algorithms; gate-referred 1/f charge-noise effects are also analyzed through the resulting coherence time.

What carries the argument

Three-dimensional Poisson and Schrödinger solvers followed by a many-body solver to extract exchange interactions and their sensitivity to bias variations, then master-equation solution for gate fidelity.

If this is right

  • Millivolt-level bias variations at plunger and middle barrier gates reduce fidelity below 99%.
  • Gate-referred 1/f charge noise shortens coherence time.
  • Nanosheet platforms require precise bias control to reach fault-tolerant thresholds.
  • Exchange energy must be evaluated under realistic process and voltage spreads.

Where Pith is reading between the lines

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

  • Tighter voltage regulation or on-chip calibration circuits may be needed to keep bias fluctuations below the millivolt scale.
  • Statistical variation across an array of nanosheet qubits would determine whether the sensitivity observed in single devices prevents large-scale integration.
  • Alternative gate layouts that reduce exchange dependence on middle-barrier voltage could be tested to relax the observed constraint.

Load-bearing premise

The three-dimensional Poisson-Schrödinger solvers and many-body solver accurately capture the exchange interaction and its sensitivity to bias variations in real nanosheet devices.

What would settle it

Fabricate nanosheet double quantum dot devices, apply controlled millivolt bias shifts to plunger and middle barrier gates during two-qubit gate operation, and measure whether the observed fidelity falls below 99%.

Figures

Figures reproduced from arXiv: 2606.32030 by Hiu Yung Wong, Sarah Dweik, Trung Nguyen.

Figure 1
Figure 1. Figure 1: Top: 3D view of the DQD nanosheet device with a silicon channel, n [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. Figure 2 [PITH_FULL_IMAGE:figures/full_fig_p002_2.png] view at source ↗
Figure 4
Figure 4. Figure 4: DQD exchange interaction J and confined electron number as a function of VB2 for VP12 = 0.595V ± 1% [PITH_FULL_IMAGE:figures/full_fig_p003_4.png] view at source ↗
Figure 7
Figure 7. Figure 7: DQD exchange interaction J and confined electron number as a function of VB2 for LB = 10.00 nm ± 10% [PITH_FULL_IMAGE:figures/full_fig_p003_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: DQD exchange interaction J and confined electron number as a function of VB2 for LP = 12.00 nm ± 8% [PITH_FULL_IMAGE:figures/full_fig_p003_8.png] view at source ↗
Figure 11
Figure 11. Figure 11: Coherence time T2 as a function of voltage-noise standard deviation [PITH_FULL_IMAGE:figures/full_fig_p004_11.png] view at source ↗
Figure 10
Figure 10. Figure 10: Gate fidelity under ± mV bias fluctuations. The circle represents ideal operation; triangles and inverted triangles show fidelity changes due to the applied voltage perturbations [PITH_FULL_IMAGE:figures/full_fig_p004_10.png] view at source ↗
read the original abstract

Silicon spin qubits are promising for large-scale quantum-computer integration because they can fully leverage the well-developed semiconductor infrastructure. However, the low fidelity of two-qubit entanglement gates remains a key barrier to large-scale integrations. Recent simulations of silicon spin-qubit two-qubit gates have been performed on silicon-on-insulator (SOI) platforms, while nanosheet-based charge-qubit work has been limited to single-qubit operation using a two-dimensional Schr\"odinger approximation. In this work, we study silicon spin-qubit double quantum dots built on nanosheet technology using the Quantum Technology Computer-Aided Design (QTCAD) simulation suite to run three-dimensional Poisson and Schroedinger solvers, followed by a many-body solver to extract exchange interactions. We evaluate the exchange energy sensitivity to process and bias variations and then use QuTiP to solve the master equation for a two-qubit gate. The results show that millivolt-level bias variations at the plunger and middle barrier gates can reduce the gate fidelity below 99%, a common threshold target for many fault-tolerant quantum-computing algorithms. Gate-referred 1/f charge-noise effects are also analyzed through the resulting coherence time.

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 / 2 minor

Summary. The manuscript presents a computational study of two-qubit spin-qubit gates realized in double quantum dots on nanosheet technology. The authors employ the QTCAD package to perform three-dimensional Poisson and Schrödinger solves followed by a many-body calculation to extract the exchange interaction J, then integrate the two-qubit master equation in QuTiP to obtain gate fidelities under static bias offsets and 1/f charge noise. The central numerical claim is that millivolt-scale variations at the plunger and middle-barrier gates drive the CZ or CNOT fidelity below the 99 % threshold commonly required for fault-tolerant algorithms.

Significance. If the QTCAD model chain accurately reproduces real nanosheet devices, the work supplies a concrete, device-specific estimate of the voltage-control precision needed for scalable silicon spin qubits. The use of full 3D electrostatics rather than the 2D Schrödinger approximation employed in earlier nanosheet charge-qubit papers is a methodological advance. The study also supplies a reproducible workflow (QTCAD + QuTiP) that other groups can apply to different process stacks, which is a positive contribution to the variability literature.

major comments (2)
  1. [Abstract / §3] Abstract and §3 (Simulation workflow): The headline result that mV-level bias variations reduce fidelity below 99 % rests entirely on the output of the QTCAD 3D Poisson-Schrödinger + many-body solver. No comparison to experimental exchange values from nanosheet devices, no convergence study with respect to mesh density or many-body basis size, and no cross-check against an independent solver are reported; this directly affects the credibility of the quantitative fidelity numbers.
  2. [§4] §4 (Fidelity results): The master-equation fidelities are stated without accompanying statistical uncertainties arising from the extracted J values or from the charge-noise spectral density; without these, it is impossible to judge whether the reported crossing of the 99 % threshold is robust or an artifact of a particular noise realization.
minor comments (2)
  1. [Figures 4-6] Figure captions and text should explicitly state the target two-qubit gate (CZ or CNOT) and the precise pulse sequence used in the QuTiP integration.
  2. [Introduction] The distinction between the present spin-qubit study and the cited prior nanosheet charge-qubit work should be drawn more sharply in the introduction to avoid reader confusion.

Simulated Author's Rebuttal

2 responses · 1 unresolved

We thank the referee for the constructive comments on our manuscript. We address each major point below, indicating where revisions will be made and where limitations of the current study prevent full compliance.

read point-by-point responses

  1. Referee: [Abstract / §3] Abstract and §3 (Simulation workflow): The headline result that mV-level bias variations reduce fidelity below 99 % rests entirely on the output of the QTCAD 3D Poisson-Schrödinger + many-body solver. No comparison to experimental exchange values from nanosheet devices, no convergence study with respect to mesh density or many-body basis size, and no cross-check against an independent solver are reported; this directly affects the credibility of the quantitative fidelity numbers.

    Authors: We agree that the quantitative fidelity claims rely on the QTCAD solver chain. The manuscript is a computational study; experimental exchange data for nanosheet spin qubits are not yet available in the literature, precluding direct comparison. We will add a convergence study with respect to mesh density and many-body basis size to the revised §3, along with explicit statements of model assumptions and limitations. A cross-check against an independent solver is not feasible within the scope and resources of this work. revision: partial

  2. Referee: [§4] §4 (Fidelity results): The master-equation fidelities are stated without accompanying statistical uncertainties arising from the extracted J values or from the charge-noise spectral density; without these, it is impossible to judge whether the reported crossing of the 99 % threshold is robust or an artifact of a particular noise realization.

    Authors: We accept this criticism. In the revised manuscript we will propagate uncertainties from the extracted J values (arising from bias variations) and from the 1/f noise spectral density parameters into the fidelity calculations, presenting them as error estimates or ranges in §4 to demonstrate robustness of the 99 % threshold crossing. revision: yes

standing simulated objections not resolved
  • Direct comparison to experimental exchange values from nanosheet devices, as no such published data exist for the devices modeled.

Circularity Check

0 steps flagged

No significant circularity; forward simulation only

full rationale

The paper reports a purely computational workflow: 3D Poisson-Schrödinger solvers plus many-body solver in QTCAD extract exchange energies from device geometry and bias voltages, followed by QuTiP master-equation integration to obtain gate fidelity. No parameter is fitted to the reported fidelity or exchange values and then re-presented as an independent prediction; the headline result is the direct numerical output of the described simulation chain. No self-citation, uniqueness theorem, or ansatz is invoked to close any derivation loop. The derivation is therefore self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only; no explicit free parameters, axioms, or invented entities are stated or can be extracted.

pith-pipeline@v0.9.1-grok · 5745 in / 1042 out tokens · 29819 ms · 2026-07-01T04:52:47.123998+00:00 · methodology

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Reference graph

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