Session KH: KH Mini-Symposium: Quantum Information Science and Technology for Nuclear Physics I

Results from the NSAC report: Nuclear Physics and Quantum Information Science

NSAC was charged with providing a report to DOE and NSF that assessed the potential impact that quantum information science (QIS) may have on nuclear physics research programs and new opportunities that may arise, and the identification of unique contributions that Nuclear Physics research could make to the development of QIS. The NSAC QIS subcommittee delivered its report during the NSAC meeting in October 2019. Scientific highlights, conclusions and recommendations of this report will be discussed. Subcommittee Membership: Douglas Beck, Amber Boehnlein, Joseph Carlson, David Dean, Matthew Dietrich, William Fairbanks Jr., Joseph Formaggio, Markus Greiner, David Hertzog, Christine Muschik, Jeffrey Nico, Alan Poon, John Preskill, Sofia Quaglioni, Krishna Rajagopal and Martin Savage.   

Real-time chiral dynamics from a digital quantum simulation

The chiral magnetic effect in a strong magnetic field can be described using the chiral anomaly in the $(1+1)$-dimensional massive Schwinger model with a time-dependent $\theta$-term. We perform a digital quantum simulation of the model at finite $\theta$-angle and vanishing gauge coupling using an IBM-Q digital quantum simulator, and observe the corresponding vector current induced in a system of relativistic fermions by a global {\it chiral quench} -- a sudden change in the chiral chemical potential or $\theta$-angle. At finite fermion mass, there appears an additional contribution to this current that stems from the non-anomalous relaxation of chirality. Our results are relevant for the real-time dynamics of chiral magnetic effect in heavy ion collisions and in chiral materials, as well as for modeling high-energy processes at hadron colliders.   

Quantum Algorithms for Simulating the Lattice Schwinger Model

The Schwinger model is a testbed for the study of quantum gauge field theories. We give scalable, explicit digital quantum algorithms to simulate the lattice Schwinger model in both NISQ and fault-tolerant settings. In particular, we analyze low-order Trotter formula simulations of the Schwinger model, using recently derived commutator bounds, and give upper bounds on the resources needed for simulations. We give scalable measurement schemes and algorithms to estimate observables which we cost in both settings by assuming a simple target observable: the mean pair density. Finally, we bound the root-mean-square error in estimating this observable via simulation as a function of the diamond distance between the ideal and actual CNOT channels. This work provides a rigorous analysis of simulating the Schwinger model, while also providing benchmarks against which subsequent simulation algorithms can be tested.   

Benchmarking Non-Abelian Lattice Gauge Theories with NISQ Algorithms

Non-Abelian gauge theories are at the heart of the Standard Model of Particle Physics, and can be treated numerically with a lattice regularization scheme. Computing the real-time dynamics of lattice gauge theories remains computationally intractable, as the only known classical algorithms are NP-complex. The discovery of polynomial quantum simulation algorithms [Lloyd, 1995], represents a promising alternative, provided scalable quantum computing platforms can be engineered. \small(1+1)\normalsize-dimensional \textit{\small SU(2) \normalsize fermionic gauge theory} (\small{SU2FGT}\normalsize) can be efficiently mapped to a quantum platform with limited qubit-connectivity, and represents the perfect testbed for benchmarking classically intractable computations on \textit{noisy intermediate-scale quantum} (\small{NISQ}\normalsize) hardware. In this work, the real-time dynamics of \small(1+1)\normalsize-\small SU2FGT \normalsize is simulated on \small IBM's \normalsize\text{\small{$5$}}-qubit quantum platform family. To amplify the range of accessible real-time dynamics, a set of newly-developed hybrid quantum algorithms are applied to subsidize coherence-limited quantum hardware with classical resources.   

Efficient excited state preparation for linear response

Quantum computing holds a huge promise in simulating the dynamics of quantum systems. In this work, we are interested in the preparation of excited states, which is a necessary step in studying quantum dynamics problems, and we describe two different strategies. The first strategy approximates the Hermitian excitation operator $O$ by $\sin(\gamma O)/\gamma$, valid for small $\gamma$, using the time evolution operator and one additional qubit. The second strategy performs the excitation operation in an exact way using the linear combination of unitary (LCU) algorithm. We apply these two strategies to a toy version of the nuclear $n(p,d)\gamma$ reaction, and perform on the IBM machine. We show that the LCU based method is more efficient than the first method in most cases and is asymptotically more resilient to depolarizing noise.   

Quantum Computing for Antineutrino Event Reconstruction

PROSPECT is an antineutrino detector located above ground at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The energy spectrum of antineutrinos emitted from the reactors is measured by using a delayed coincidence technique through the inverse-beta-decay (IBD) interaction. The efficiency of current methods used to reconstruct antineutrino events through the signatures of the positron annihilation and neutron capture in the liquid scintillator is very low. A potential alternative to improve both reconstruction efficiency and computing time is using quantum computing. In this way, the problem of matching detector pulses consistent with the positron and neutron signals is cast to an "earth movers distance" problem. The latter can then be encoded into an Ising Hamiltonian, whose ground state can be computed in quantum annealers such as the D-Wave quantum computer processor.   

Optimal Control for the Quantum Simulation of Nuclear Dynamics

Real time simulations of quantum systems hold the key to modeling and understanding the dynamics and responses of strongly interacting many-body systems such as atomic nuclei and their interactions with other matter. Classical calculations of such systems are plagued by an exponential growth of particle configurations and aggressively more difficult to handle sign problems. Quantum computing offers a pathway to directly simulate the real time evolution of these systems with polynomial scaling and no sign problem. However, current quantum computation is too noisy to implement and execute the formal quantum computing algorithms that have been proposed to compute such real time dynamics. This limitation often manifests itself as a limit in the number of quantum gates that can be applied before the QPU enters a decoherent state and all information about the simulated dynamics is lost. We demonstrate an alternative efficient high-fidelity encoding of the nuclear dynamics onto a QPU and apply it to the real-time simulation of neutron scattering using a Hamiltonian derived from chiral effective field. I will present both simulated data and real data taken on the Lawrence Livermore National Lab’s quantum testbed.