Using Tensor Lattice Field Theory (for a recent review see arXiv:2010.06539),
we construct a gauge-invariant transfer matrix for compact scalar electrodynamics in arbitrary dimensions. We propose a noise-robust way to implement Gauss's law. We discuss quantum simulation experiments with Rydberg atoms where the electric field Hilbert space is approximated by a spin-1 triplet. We propose two...
The interpretation of measurements from high energy collisions at experiments like the Large Hadron Collider (LHC) relies heavily on the performance of full event generators, specifically their accuracy and speed in simulating complex multi-particle final states. With the rapid and continuous improvement in quantum computers, these devices present an exciting opportunity for high energy...
The light-front quantization provides a natural framework for digital quantum simulation of quantum field theory. In our work (2002.04016, 2105.10941), we demonstrated this by developing quantum algorithms based on simulating time evolution and adiabatic state preparation. We discussed various ways of encoding physical states in the quantum computer and provided resource estimates for Yukawa...
Oscillating neutrino beams exhibit quantum coherence over distances of thousands of kilometers. Their unambiguously quantum nature suggests an appealing test system for direct quantum simulation. Such techniques may enable presently analytically intractable calculations involving multi-neutrino entanglements, such as collective neutrino oscillations in supernovae, but only once oscillation...
In the context of high-energy physics, perturbation theory is the most widely used strategy for extracting accurate theoretical predictions. However, higher-order contributions require the evaluation of complicated multi-loop Feynman integrals, which constitute a serious bottleneck in current computational frameworks. In this talk we present the first application of a quantum algorithm to...
Quantum computers have the potential to speed up certain computational tasks. A possibility this opens up within the field of machine learning is the use of quantum techniques that may be inefficient to simulate classically but could provide superior performance in some tasks. Machine learning algorithms are ubiquitous in particle physics and as advances are made in quantum machine learning...
We study the quantum counterpart of Support Vector Machines, namely Quantum Support Vector Machines (QSVΜ), and a Quantum Machine Learning (QML) architecture that combines a classical encoder neural network and a Variation Quantum Circuit (VQC) into a single model. That is, a Neural Network Variational Quantum Circuit (NNVQC) for the binary classification of High Energy Physics data....
The identification of jets coming from heavy-flavour quarks, namely $b$- and $c$-quarks, is an important and non-trivial task at the LHC experiments. The classification of jets coming from $b$- and $\bar{b}$-quarks at the LHCb experiment allows to perform physics measurements, such as the forward-central charge asymmetry, to constrain the Standard Model predictions and/or find possible...
Quantum Machine Learning is among others the most promising application on near-term quantum devices which possess the potential to combat problems faster than traditional computers. Classical Machine Learning (ML) is taking up a significant role in particle physics to speed up detector simulations. Generative Adversarial Networks (GANs) have scientifically proven to achieve a similar level of...
The Large Hadron Collider is a very complex machine providing millions of collisions per second. Simulating events to compare theory and data requires a lot of computing power, in particular for the event generation and the whole analysis toolchain. Machine-learning techniques may provide new avenues to optimize the computing power. This talk presents a novel quantum generator in the context...
CERN has recently started its Quantum Technology Initiative in order to investigate the use of quantum technologies in High Energy Physics (HEP). A three-year roadmap and research programme has been defined in collaboration with the HEP and quantum-technology research communities. In this context, initial pilot projects have been set up at CERN in collaboration with other HEP institutes...
Currently, the vast amount of data presents a challenge for high-energy physics experiments, and most data most be discarded, keeping only data which passes templated triggers. Since we do not know the form new physics will take, these templated triggers may be excluding interesting events. This problem will only be exacerbated in the future as the size, intensity, and complexity of the...
High-energy physics is replete with hard computational problems and it is one of the areas where quantum computing could be used to speed up calculations. We present an implementation of likelihood-based regularized unfolding on a quantum computer. The inverse problem is recast in terms of quadratic unconstrained binary optimization (QUBO), which has the same form of the Ising hamiltonian and...
Microwave-optical quantum transducers that convert quantum information between microwave and optical frequencies with high fidelity play a crucial role in long-distance quantum networks and have promising breakthroughs in quantum sensing. High-efficiency and low-noise quantum transduction in the quantum level remains challenging in the current designs and demonstrations. At Fermilab we have...
This work generalizes the quantum amplitude amplification (Grover’s) and amplitude estimation algorithms to work with non-Boolean oracles, leading to two new algorithms. Unlike Boolean oracles, the eigenvalues of a non-Boolean oracle are not restricted to be ±1. 1) The non-Boolean amplitude amplification algorithm preferentially amplifies the amplitudes of the eigenstates based on a given...
I provide explicit circuits implementing the Kitaev–Webb algorithm for the preparation of multi-dimensional Gaussian states on quantum computers. While asymptotically efficient due to its polynomial scaling, I show that circuits implementing the preparation of one-dimensional Gaussian states and those subsequently entangling them to reproduce the required covariance matrix
differ...
Quantum Technologies and especially Quantum Computing are strongly evolving fields in HEP. There are several European Initiatives, for example the CERN QTI – Quantum Technology Initiative, as well as initiatives on national level. In Germany, DESY, in its role as the German national HEP hub, had established a Quantum Technology Task Force about one year ago. This Task Force is in the process...
To investigate the fundamental nature of matter and its interactions, particles are accelerated to very high energies and collided inside detectors, producing a multitude of other particles that are scattered in all directions. As charged particles traverse the detector, they leave signals of their passage. The problem of track reconstruction is to recover the original trajectories from these...
