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arXiv:2608.13654

Entanglement Negativity in Noisy Quantum Volume Sampling

Elijah Pelofske, Stephan Eidenbenz

quant-phSubmitted Aug 13, 2026• Announced Aug 17, 2026• 0 citations
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Abstract

The Quantum Volume protocol uses scrambling random circuits to benchmark NISQ computers. Quantum Volume is generally well-regarded as a benchmark for small, noisy, quantum computers because it requires the quantum computer to implement many non-local entangling gates within a square-shaped circuit, which incentivizes high qubit count, long qubit coherence times, and low error rates on all hardware gates. Quantum Volume circuits inherently produce high-entanglement states that are fragile to errors and decoherence. The Quantum Volume benchmark measures an observable called heavy-output-probability (HOP), where an HOP of $0.5$ corresponds to complete loss of coherence, and in the limit of system size an HOP $\approx 0.84$ for a fully coherent quantum processor. Here, we numerically study the tradeoff between depolarizing noise, entanglement as quantified by the bipartite negativity measure, and HOP in quantum volume circuits. Our results contextualize prior small scale quantum volume demonstrations on quantum computers and highlight that under depolarizing noise, due to finite system size effects heavy output probabilities can be greater than $0.5$ while the bipartite negativity entanglement has been destroyed. This implies, although improbable, that a NISQ computer could pass the Quantum Volume benchmark test threshold of $2/3$ while the underlying quantum computation has no global entanglement -- albeit only for small $n$.

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The Quantum Volume protocol uses scrambling random circuits to benchmark NISQ computers. Quantum Volume is generally well-regarded as a benchmark for small, noisy, quantum computers because it requires the quantum computer to implement many non-local entangling gates within a square-shaped circuit, which incentivizes high qubit count, long qubit coherence times, and low error rates on all hardware gates. Quantum Volume circuits inherently produce high-entanglement states that are fragile to errors and decoherence. The Quantum Volume benchmark measures an observable called heavy-output-probability (HOP), where an HOP of 0.50.50.5 corresponds to complete loss of coherence, and in the limit of system size an HOP ≈0.84\approx 0.84≈0.84 for a fully coherent quantum processor. Here, we numerically study the tradeoff between depolarizing noise, entanglement as quantified by the bipartite negativity measure, and HOP in quantum volume circuits. Our results contextualize prior small scale quantum volume demonstrations on quantum computers and highlight that under depolarizing noise, due to finite system size effects heavy output probabilities can be greater than 0.50.50.5 while the bipartite negativity entanglement has been destroyed. This implies, although improbable, that a NISQ computer could pass the Quantum Volume benchmark test threshold of 2/32/32/3 while the underlying quantum computation has no global entanglement -- albeit only for small nnn.
Quantum entanglement is a central resource for quantum computation and state transfer, yet the usefulness of multipartite entanglement depends on how rapidly coherence and nonclassical correlations degrade as the register size and communication depth increase. This methodology paper develops a reproducible density-matrix simulation for studying entanglement and information transfer in multi-qubit systems. GHZ and W states containing 3, 4, 5, 6 and 8 qubits are generated and exposed to independent local depolarizing noise. State fidelity and bipartite negativity are used to quantify preservation of the prepared resource, while an entanglement-assisted multi-hop teleportation model measures the fidelity of transferred single-qubit information. The simulation shows a systematic decrease in state fidelity and negativity with increasing register size at a fixed local error probability. At a local depolarizing probability of 0.02, GHZ fidelity decreases from 0.941 for three qubits to 0.852 for eight qubits, whereas W-state fidelity decreases from 0.943 to 0.877. In a separate transfer experiment with an effective error probability of 0.10 per teleportation hop, average transfer fidelity decreases from 0.933 after one hop to 0.745 after five hops, while remaining above the classical benchmark of 2/3. These results illustrate how multipartite entanglement quality; noise accumulation and path depth jointly determine the reliability of information transfer in multi-qubit computing architectures.
The quantum volume test is a full-system benchmark for quantum computers that is sensitive to qubit number, fidelity, connectivity, and other quantities believed to be important in building useful devices. The test was designed to produce a single-number measure of a quantum computer's general capability, but a complete understanding of its limitations and operational meaning is still missing. We explore the quantum volume test to better understand its design aspects, sensitivity to errors, passing criteria, and what passing implies about a quantum computer. We elucidate some transient behaviors the test exhibits for small qubit number including the ideal measurement output distributions and the efficacy of common compiler optimizations. We then present an efficient algorithm for estimating the expected heavy output probability under different error models and compiler optimization options, which predicts performance goals for future systems. Additionally, we explore the original confidence interval construction and show that it underachieves the desired coverage level for single shot experiments and overachieves for more typical number of shots. We propose a new confidence interval construction that reaches the specified coverage for typical number of shots and is more efficient in the number of circuits needed to pass the test. We demonstrate these savings with a Q V = 2 10 experimental dataset collected from Quantinuum System Model H1-1. Finally, we discuss what the quantum volume test implies about a quantum computer's practical or operational abilities especially in terms of quantum error correction.
The process by which open quantum systems thermalize with an environment is both of fundamental interest and relevant to noisy quantum devices. As a minimal model of this process, we consider a qudit chain evolving under local random unitaries and local depolarization channels. After mapping to a statistical mechanics model, the depolarization (noise) acts like a symmetry-breaking field, and we argue that it causes the system to thermalize within a timescale independent of system size. We show that various bipartite entanglement measures---mutual information, operator entanglement, and entanglement negativity---grow at a speed proportional to the size of the bipartition boundary. As a result, these entanglement measures obey an area law: Their maximal value during the dynamics is bounded by the boundary instead of the volume. In contrast, if the depolarization only acts at the system boundary, then the maximum value of the entanglement measures obeys a volume law. We complement our analysis with scalable simulations involving Clifford gates, for both one- and two-dimensional systems.
Random circuit sampling (RCS) remains one of the most competitive frameworks for demonstrating quantum advantage in near-term noisy intermediate-scale quantum (NISQ) hardware. Unfortunately, absent error-correction, existing benchmarks to characterize these experiments, like linear cross-entropy, have been classically spoofed due to noise. Because of this, there are interesting regimes, like shallow-depth random quantum circuits, where sampling is plausibly classically intractable, but no existing benchmark can distinguish between a noisy quantum computer and an adversarial classical spoofer. In this paper, we demonstrate that the nonlinear cross-entropy provides a sample-efficient benchmark for shallow-depth all-to-all random quantum circuits whose score cleanly separates noisy quantum computers from state-of-the-art classical spoofers, even in the presence of depolarizing noise. Further, we develop a binary classifier based on the notion of heavy output generation that features logarithmic sample complexity at short depth. Our evidence comes from exact analytic expressions for all-to-all Brownian circuit ensembles derived using replica tricks, and numerical simulations that corroborate these results for discrete Haar-random unitary circuits.
As quantum processors grow, new performance benchmarks are required to capture the full quality of the devices at scale. While quantum volume is an excellent benchmark, it focuses on the highest quality subset of the device and so is unable to indicate the average performance over a large number of connected qubits. Furthermore, it is a discrete pass/fail and so is not reflective of continuous improvements in hardware nor does it provide quantitative direction to large-scale algorithms. For example, there may be value in error mitigated Hamiltonian simulation at scale with devices unable to pass strict quantum volume tests. Here we discuss a scalable benchmark which measures the fidelity of a connecting set of two-qubit gates over NNN qubits by measuring gate errors using simultaneous direct randomized benchmarking in disjoint layers. Our layer fidelity can be easily related to algorithmic run time, via γγγ defined in Ref.\cite{berg2022probabilistic} that can be used to estimate the number of circuits required for error mitigation. The protocol is efficient and obtains all the pair rates in the layered structure. Compared to regular (isolated) RB this approach is sensitive to crosstalk. As an example we measure a N=80 (100)N=80~(100)N=80 (100) qubit layer fidelity on a 127 qubit fixed-coupling "Eagle" processor (ibm\_sherbrooke) of 0.26(0.19) and on the 133 qubit tunable-coupling "Heron" processor (ibm\_montecarlo) of 0.61(0.26). This can easily be expressed as a layer size independent quantity, error per layered gate (EPLG), which is here 1.7×10−2(1.7×10−2)1.7\times10^{-2}(1.7\times10^{-2})1.7×10−2(1.7×10−2) for ibm\_sherbrooke and 6.2×10−3(1.2×10−2)6.2\times10^{-3}(1.2\times10^{-2})6.2×10−3(1.2×10−2) for ibm\_montecarlo.
The advent of noisy intermediate-scale quantum (NISQ) devices has not only opened up new possibilities to studying quantum computational benefits, but it has also presented new challenges associated with noise and short coherence times. Entanglement is one of the inherent resources that can be used to perform quantum computation and implement the performance and reliability of quantum algorithms. This paper looks at entanglement dynamics in NISQ machines subjected to natural noises. The study focuses on the problem of examining the role of various noise channels in the creation, dynamics, and decay of the entanglement during quantum operations, such as depolarizing, amplitude damping, and phase damping. The study is based on theoretical modeling and numerical simulations of multi-qubit quantum circuits to determine the stability of entangled states with respect to circuit depth and intensity of noise. Concurrence and von Neumann entropy are examples of entanglement measures that are used to characterize correlations between qubits as well as to trace the dynamics of these correlations across computational interactions. The results show that noise has major impacts on entanglement distribution, which tends to cause rapid decays in highly entangled states with increase in circuit complexity. The findings, however, also show that there are some circuit architectures and error-mitigation schemes that can somewhat sustain entanglement with moderate levels of noise. The paper also emphasizes the relevance of minimalizing sequence of gates, and reduced circuit depth in an effort to preserve useful entanglement in present-day quantum hardware. These observations help in understanding the behaviour of quantum correlations better in real world quantum devices and provide a way of developing more resilient quantum algorithms that would work on NISQ systems. In general, the article offers a systematic view on entanglement behavior in disordered quantum systems and highlights its value in the development of quantum computing applications in the near term.