Partonic collinear structure by quantum computing

Li, Tianyin; Guo, Xingyu; Lai, Wai Kin; Liu, Xiaohui; Wang, Enke; Xing, Hongxi; Zhang, Dan-Bo; Zhu, Shi-Liang

doi:10.1103/physrevd.105.l111502

Cited by 27 publications

(9 citation statements)

References 60 publications

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“…( 18) and the definitions of Q, M , and Λ in eqs. (29)(30)(31), it can be seen that if |ψ 1 = |a g |k q |Ω U and |ψ 2 = |b g |l q |Ω U then…”

Section: Quark-gluon Interaction Gate Qmentioning

confidence: 99%

“…While most of that exploration has focused on the experimental side of highenergy physics, the last few years have also seen the emergence of applications on various topics in high-energy theory. These range from parton distribution functions (PDFs) [28,29] to amplitudes [30][31][32][33][34], effective field theory [35], cross-section computations [25], parton showers [30,[36][37][38], and event generation [38][39][40].…”

Section: Introductionmentioning

confidence: 99%

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Quantum simulation of colour in perturbative quantum chromodynamics

Chawdhry¹,

Pellen²

2023

Preprint

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Quantum computers are expected to give major speed-ups for the simulation of quantum systems. In this work, we present quantum gates that simulate the colour part of the interactions of quarks and gluons in perturbative quantum chromodynamics (QCD). As a first application, we implement these circuits on a simulated noiseless quantum computer and use them to calculate colour factors for various examples of Feynman diagrams. This work constitutes a first key step towards a quantum simulation of generic scattering processes in perturbative QCD.

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“…( 18) and the definitions of Q, M , and Λ in eqs. (29)(30)(31), it can be seen that if |ψ 1 = |a g |k q |Ω U and |ψ 2 = |b g |l q |Ω U then…”

Section: Quark-gluon Interaction Gate Qmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantum simulation of colour in perturbative quantum chromodynamics

Chawdhry¹,

Pellen²

2023

Preprint

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“…This theoretical groundwork is bolstered by several instances of specifically constructed QML circuits presenting significantly more efficient solutions than classically possible to specially designed problems [40][41][42][43]. QNNs have already been successfully applied to relatively limited high-energy physics problems [21,25,[44][45][46][46][47][48], along non-QML approaches [49][50][51][52][53]. However, to our knowledge, there has not yet been an attempt to construct an invertible QNN that can be used as a density estimator through its invertibility for generative tasks.…”

Section: Introductionmentioning

confidence: 99%

Generative Invertible Quantum Neural Networks

Rousselot¹,

Spannowsky²

2023

Preprint

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Invertible Neural Networks (INN) have become established tools for the simulation and generation of highly complex data. We propose a quantum-gate algorithm for a Quantum Invertible Neural Network (QINN) and apply it to the LHC data of jet-associated production of a Z-boson that decays into leptons, a standard candle process for particle collider precision measurements. We compare the QINN's performance for different loss functions and training scenarios. For this task, we find that a hybrid QINN matches the performance of a significantly larger purely classical INN in learning and generating complex data.

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“…Some of these novel proposals to use quantum technologies have ranged from the simulation of scalar [2][3][4][5][6][7][8][9][10][11], fermionic [12][13][14] and gauge field theories [15][16][17][18][19][20][21][22][23][24][25][26][27] to thermal systems [28] and the thermalization of nonequilibrium systems [29][30][31]. Beside field theory based simulations, they have also been applied to specific topics such as nuclear structure [32][33][34][35][36][37], neutrino oscillation [38] and string theory [39]. Concerning collider oriented physics, these technologies have, for example, been used to simulate hard probes like heavy flavors [40] and jets [41,42], optimize parton showers [43][44][45] and jet clustering algorithms [46][47]…”

Section: Introductionmentioning

confidence: 99%

Medium induced jet broadening in a quantum computer

Barata¹,

Du²,

Li³

et al. 2022

Preprint

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QCD jets provide one of the best avenues to extract information about the quark-gluon plasma produced in the aftermath of ultra relativistic heavy ions collisions. The structure of jets is determined by multiparticle quantum interference hard to tackle using perturbative methods. When jets evolve in a QCD medium this interference pattern is modified, adding another layer of complexity. By taking advantage of the recent developments in quantum technologies, such effects might be better understood via direct quantum simulation of jet evolution. In this work, we introduce a precursor to such simulations. Based on the light-front Hamiltonian formalism, we construct a digital quantum circuit that tracks the evolution of a single hard probe in the presence of a stochastic color background. In terms of the jet quenching parameter q, the results obtained using classical simulators of ideal quantum computers agree with known analytical results. With this study, we hope to provide a baseline for future in-medium jet physics studies using quantum computers.

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Partonic collinear structure by quantum computing

Cited by 27 publications

References 60 publications

Quantum simulation of colour in perturbative quantum chromodynamics

Quantum simulation of colour in perturbative quantum chromodynamics

Generative Invertible Quantum Neural Networks

Medium induced jet broadening in a quantum computer

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