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A Quantum Algorithm for Model-Independent Searches for New Physics
High Energy Physics - Phenomenology · Submitted 4 Mar 2020
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim We demonstrate that our test statistic outperforms some of the most commonly used goodness-of-fit tests.
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The abstract, sentence by sentence
We propose a novel quantum technique to search for unmodeled anomalies in multidimensional binned collider data. We propose associating an Ising lattice spin site with each bin, with the Ising Hamiltonian suitably constructed from the observed data and a corresponding theoretical expectation. In order to capture spatially correlated anomalies in the data, we introduce spin-spin interactions between neighboring sites, as well as self-interactions. The ground state energy of the resulting Ising Hamiltonian can be used as a new test statistic, which can be computed either classically or via adiabatic quantum optimization. We demonstrate that our test statistic outperforms some of the most commonly used goodness-of-fit tests. The new approach greatly reduces the look-elsewhere effect by exploiting the typical differences between statistical noise and genuine new physics signals.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | We propose a novel quantum technique to search for unmodeled anomalies in multidimensional binned collider data. | contribution 1.00 | 0.74 | 0.24 | asserted 0.90 |
| s1 | We propose associating an Ising lattice spin site with each bin, with the Ising Hamiltonian suitably constructed from the observed data and a corresponding theoretical expectation. | method 0.89 | 0.75 | 0.07 | asserted 0.95 |
| s2 | In order to capture spatially correlated anomalies in the data, we introduce spin-spin interactions between neighboring sites, as well as self-interactions. | method 0.92 | 0.85 | 0.04 | asserted 0.99 |
| s3 | The ground state energy of the resulting Ising Hamiltonian can be used as a new test statistic, which can be computed either classically or via adiabatic quantum optimization. | method 0.88 | 0.61 | 0.15 | asserted 0.91 |
| s4 | We demonstrate that our test statistic outperforms some of the most commonly used goodness-of-fit tests. | result 1.00 | 0.94 | 0.40 | asserted 1.00 |
| s5 | The new approach greatly reduces the look-elsewhere effect by exploiting the typical differences between statistical noise and genuine new physics signals. | result 0.56 | 0.76 | 0.30 | asserted 1.00 |
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The paper
Original abstract
We propose a novel quantum technique to search for unmodeled anomalies in multidimensional binned collider data. We propose associating an Ising lattice spin site with each bin, with the Ising Hamiltonian suitably constructed from the observed data and a corresponding theoretical expectation. In order to capture spatially correlated anomalies in the data, we introduce spin-spin interactions between neighboring sites, as well as self-interactions. The ground state energy of the resulting Ising Hamiltonian can be used as a new test statistic, which can be computed either classically or via adiabatic quantum optimization. We demonstrate that our test statistic outperforms some of the most commonly used goodness-of-fit tests. The new approach greatly reduces the look-elsewhere effect by exploiting the typical differences between statistical noise and genuine new physics signals.
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How the literature uses it
9 arXiv papers cite this in 10 sentences
Papers citing it · 6 sentences without a confident label
Cites it as background 4 papers
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There have already been several approaches to marry ML classifiers and statistical tests, see e.g. [ref] .
A method for approximating optimal statistical significances with machine-learned likelihoods · Similar approaches in the literature · 1.00
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However a particularly difficult aspect of this programme is the preparation of scattering states [ref] , with several works having proposed a hybrid classical/quantum approach to solving this problem [ref] .
Quantum Computing for Quantum Tunnelling · Introduction · 0.82
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Calculation of multi-particle interactions [ref] accomplished with the mapping of field theories onto quantum walks [ref] or a combination of quantum and classical ideas [ref] have also all been done using models built from quantum gates.
Unsupervised Event Classification with Graphs on Classical and Photonic Quantum Computers · Introduction · 0.87
What it cites · 19 sentences without a confident label
Cites as background 21 papers
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These include traditional bump-hunting methods, edge detection techniques [ref] and recent machine-learning based approaches [ref] .
Anomaly Detection with Density Estimation · Introduction · 0.91
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These include traditional bump-hunting methods, edge detection techniques [ref] and recent machine-learning based approaches [ref] .
A robust anomaly finder based on autoencoders · Introduction · 0.91
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These include traditional bump-hunting methods, edge detection techniques [ref] and recent machine-learning based approaches [ref] .
Uncovering latent jet substructure · Introduction · 0.91
Discussion
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