Observable Estimation in the Absence of Classical Verification
- URL: http://arxiv.org/abs/2607.25998v1
- Date: Tue, 28 Jul 2026 17:14:26 GMT
- Title: Observable Estimation in the Absence of Classical Verification
- Abstract summary: We introduce a framework for the independent validation of quantum estimates.<n>We show how this framework can be extended to place accuracy bounds on quantum estimates.<n>These results establish a route towards trusted quantum computation for scientific discovery.
- Score: 1.6271078211560834
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The predictive success of quantum mechanics underpins many areas of modern science, even as the exact simulation of large, interacting quantum systems remains beyond the reach of classical computation. This success has been enabled by the remarkable advancement of scalable numerical approximation methods, which often demonstrate practical accuracy despite the absence of formal guarantees. As quantum simulation pushes into regimes where these approximations struggle, a fundamental challenge arises: How can quantum outcomes be trusted when reliable classical benchmarks are unavailable? Here, we establish a framework for the independent validation of quantum estimates in this setting and present evidence that they provide the most credible result among several considered methods, in the absence of an immediately accessible ground-truth solution. We apply our framework to the semi-scrambling dynamics of a physical model that strains several leading classical simulation methods yet remains experimentally accessible, in part through our introduction of the \textit{operator Loschmidt echo}. We systematically design a series of experiments using quantum heuristics that, taken together, test the underlying assumptions and provide strong confidence in the observable estimates obtained from the quantum computer. We then show how this framework can be extended to place accuracy bounds on quantum estimates via careful characterization and manipulation of the device noise, transforming the problem of validating the observable estimation to validating the noise model. These results establish a route towards trusted quantum computation for scientific discovery, independent of classical verification.
Related papers
- Learnable yet not simulable: a quantum resource theory of learning models [57.695822250391906]
It remains unclear which quantum resource governs the classical learnability of quantum circuits.<n>We study the expectation-value functions of families of tunable quantum circuits.<n>These results establish a quantitative resource-theoretic framework for delineating the boundary between classical simulation and learning.
arXiv Detail & Related papers (2026-08-03T14:48:03Z) - Benchmarking quantum simulation at scale [0.8264316322451414]
We propose a scalable verification scheme for non-equilibrium quantum simulation based on stabilizer scars.<n>We show that the fidelity of quantum simulating these states bounds the fidelity of classically intractable simulations.
arXiv Detail & Related papers (2026-07-15T18:00:01Z) - Certifying coherence in quantum devices under classical control [33.72751145910978]
We prove that coherence can be fully characterised through a hierarchy of semidefinite programs.<n>For the important special case of qubits, we exploit conceptual connections with the theory of joint measurability.<n>We apply these methods to determine whether quantum channels are able to preserve coherence or are inherently coherence-breaking.
arXiv Detail & Related papers (2026-06-02T14:20:45Z) - Contextuality of quantum non-demolition measurement via state discrimination [1.4494771112934626]
We theoretically demonstrate contextual features inherent in the structure of quantum non-demolition measurements.<n>Our results broaden the scope of observing nonclassicality in quantum systems and ultimately contribute to the advancement of various quantum technologies.
arXiv Detail & Related papers (2026-03-30T00:15:45Z) - Bounded-Error Quantum Simulation via Hamiltonian and Lindbladian Learning [1.7515811671331791]
We introduce a general framework for bounded-error quantum simulation.<n>It provides predictions for many-body observables with experimentally quantifiable uncertainties.<n>We demonstrate this framework on trapped-ion quantum simulators implementing long-range Ising interactions with up to 51 ions.
arXiv Detail & Related papers (2025-11-28T17:33:59Z) - Exponential distillation of dominant eigenproperties [0.0]
Estimating observable expectation values in eigenstates of quantum systems has a broad range of applications.<n>We develop a hybrid quantum-classical algorithm that enables the estimation of an arbitrary observable expectation value in an eigenstate.
arXiv Detail & Related papers (2025-06-04T18:49:08Z) - Bayesian Quantum Amplitude Estimation [46.03321798937855]
We present BAE, a problem-tailored and noise-aware Bayesian algorithm for quantum amplitude estimation.<n>In a fault tolerant scenario, BAE is capable of saturating the Heisenberg limit; if device noise is present, BAE can dynamically characterize it and self-adapt.<n>We propose a benchmark for amplitude estimation algorithms and use it to test BAE against other approaches.
arXiv Detail & Related papers (2024-12-05T18:09:41Z) - Fast and converged classical simulations of evidence for the utility of
quantum computing before fault tolerance [0.0]
A recent quantum simulation of observables of the kicked Ising model on 127 qubits implemented circuits exceeds the capabilities of exact classical simulation.
We show that several approximate classical methods, based on sparse Pauli dynamics and tensor network algorithms, can simulate these observables orders of magnitude faster than the quantum experiment.
arXiv Detail & Related papers (2023-08-09T17:15:17Z) - Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
We explore the applicability of quantum-data learning to practical problems in high-energy physics.
We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states.
The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
arXiv Detail & Related papers (2023-06-29T18:00:01Z) - Classical Verification of Quantum Learning [42.362388367152256]
We develop a framework for classical verification of quantum learning.
We propose a new quantum data access model that we call "mixture-of-superpositions" quantum examples.
Our results demonstrate that the potential power of quantum data for learning tasks, while not unlimited, can be utilized by classical agents.
arXiv Detail & Related papers (2023-06-08T00:31:27Z) - Quantum Conformal Prediction for Reliable Uncertainty Quantification in
Quantum Machine Learning [47.991114317813555]
Quantum models implement implicit probabilistic predictors that produce multiple random decisions for each input through measurement shots.
This paper proposes to leverage such randomness to define prediction sets for both classification and regression that provably capture the uncertainty of the model.
arXiv Detail & Related papers (2023-04-06T22:05:21Z) - Anticipative measurements in hybrid quantum-classical computation [68.8204255655161]
We present an approach where the quantum computation is supplemented by a classical result.
Taking advantage of its anticipation also leads to a new type of quantum measurements, which we call anticipative.
In an anticipative quantum measurement the combination of the results from classical and quantum computations happens only in the end.
arXiv Detail & Related papers (2022-09-12T15:47:44Z) - Quantum algorithms for quantum dynamics: A performance study on the
spin-boson model [68.8204255655161]
Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator.
variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware.
We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
arXiv Detail & Related papers (2021-08-09T18:00:05Z) - Preparing random states and benchmarking with many-body quantum chaos [48.044162981804526]
We show how to predict and experimentally observe the emergence of random state ensembles naturally under time-independent Hamiltonian dynamics.
The observed random ensembles emerge from projective measurements and are intimately linked to universal correlations built up between subsystems of a larger quantum system.
Our work has implications for understanding randomness in quantum dynamics, and enables applications of this concept in a wider context.
arXiv Detail & Related papers (2021-03-05T08:32:43Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.