Other

A vibrant program has formed in recent years in various scientific disciplines to take advantage of near-term and future quantum-simulation and quantum-computing hardware to study complex quantum many-body systems, building upon the vision of Richard Feynman for quantum simulation. Such activities have recently started in nuclear and particle physics, hoping to bring new and powerful experimental and computational tools to eventually address a range of challenging problems in strongly interacting quantum field theories and nuclear many-body systems. In this talk, I review a number of important developments, including proposals for simulating strongly interacting field theories with the ultimate goal of studying strong dynamics of quarks and gluons, and of nucleons. Some of the requirements for hardware technologies that are expected to enable both the analog simulations and the digital quantum computations of these problems will be enumerated, and an experiment-theory co-development program will be motivated with an emphasis on trapped-ion platforms.

A dark matter candidate lighter than about 30 eV exhibits wave behavior in a typical galactic environment. Examples include the QCD axion as well as other axion-like-particles. We review the particle physics motivations, and discuss experimental and observational implications of the wave dynamics, including interference substructures, vortices, soliton condensation and black hole hair.

Gravitational waves provide a unique way to study the universe. From the initial direct detection of coalescing black holes in 2015, to the ground-breaking multimessenger observations of coalescing neutron stars in 2017, and continuing with the now routine detection of merging stellar remnants, gravitational wave astronomy has quickly matured into a key aspect of modern physics. After briefly discussing what we've begun to learn from the new gravitational-wave transient catalog published by the LIGO, Virgo, and KAGRA collaborations (GWTC-2), I will discuss novel tests of fundamental physics GWs enable. In particular, I will focus on our current understanding of matter effects during the inspiral of compact binaries and matter at supranuclear densities, including possible phase transitions, through tests of neutron star structure. Detailed knowledge of dynamical interactions between coalescing stars, observations of extreme relativistic astrophysical systems, terrestrial experiments, and nuclear theory provide complementary views of fundamental physics. I will show how combining aspects from all these will improve our understanding of dense matter through the example of how we can determine whether newly observed objects are neutron stars or black holes.

A standard account of the measurement chain in quantum mechanics involves a probe (itself a quantum system) coupled temporarily to the system of interest. Once the coupling is removed, the probe is measured and the results are interpreted as the measurement of a system observable. Measurement schemes of this type have been studied extensively in Quantum Measurement Theory, but they are rarely discussed in the context of quantum fields and still less on curved spacetimes. 

In this talk I will describe how measurement schemes may be formulated for quantum fields on curved spacetime within the general setting of algebraic QFT. This allows the discussion of the localisation and properties of the system observable induced by a probe measurement, and the way in which a system state can be updated thereafter. The framework is local and fully covariant, allowing the consistent description of measurements made in spacelike separated regions. Furthermore, specific models can be given in which the framework may be exemplified by concrete calculations.

I will also explain how this framework can shed light on an old problem due to Sorkin concerning "impossible measurements" in which measurement apparently conflicts with causality.

The talk is based on work with Rainer Verch [Leipzig], (Comm. Math. Phys. 378, 851–889(2020), arXiv:1810.06512; see also arXiv:1904.06944 for a summary) and a recent preprint arXiv:2003.04660 with Henning Bostelmann and Maximilian H. Ruep [York].

We present a quantum architecture based on a linear chain of trapped 171Yb+ ions with individual laser beam addressing and readout. The collective modes of motion in the chain are used to efficiently produce entangling gates between any qubit pair. In combination with a classical software stack, this becomes in effect an arbitrarily programmable and fully connected quantum computer. The system compares favorably to commercially available alternatives [2].
We use this versatile setup to perform a quantum walk algorithm that realizes a simulation of the free Dirac equation where the quantum coin determines the particle mass [3]. We are also pursuing digital simulations towards models relevant in high-energy physics among other applications. Recent results from these efforts, and concepts for expanding and scaling up the architecture will be discussed.
[1] S. Debnath et al., Nature 563:63 (2016); P. Murali et al., IEEE Micro, 40:3 (2020); [3] C. Huerta Alderete et al., Nat. Communs. 11:3720 (2020).

The idea that structure in the Universe was created from quantum mechanical vacuum fluctuations during inflation is very compelling, but unproven. Finding a test of this proposal has been challenging because the universe we observe is effectively classical. I will explain how quantum fluctuations can give rise to the density fluctuations we observe and will show that we can test this hypothesis using the statistical properties of maps of the universe.

One of the major themes of the modern condensed matter physics is the study of materials with nontrivial electronic structure topology. Particularly significant progress in this field has happened within the last decade, due to the discovery of topologically nontrivial states of matter, that have a gap in their energy spectrum, namely Topological Insulators and Topological Superconductors. In this talk I will describe the most recent work, partly my own, extending the notions of the nontrivial electronic structure topology to gapless states of matter as well, namely to semimetals and even metals. I will discuss both the theoretical concepts, and the recent experimental work, realizing these novel states of condensed matter.

In most materials, electrons fill bands, starting from the lowest kinetic energy states. The Fermi level is the boundary between filled states below and empty states above. This is the basis for our very successful understanding of how metals and semiconductors work. But what if all the electrons within a band had the same kinetic energy (this situation is called a "flat band")? Then electrons could arrange themselves so as to minimize their Coulomb repulsion, giving rise to a wide variety of possible states including superconductors and magnets. Until recently, flat bands were achieved only by applying large magnetic fields perpendicular to a 2D electron system; in this context they are known as Landau levels. Fractional quantum hall effects result from Coulomb-driven electron arrangement within a Landau level. Recently, Pablo Jarillo-Herrero of MIT and coworkers demonstrated flat minibands in graphene-based superlattices, discovering correlated insulators and superconductors at different fillings of these minibands. We have now discovered dramatic magnetic states in such superlattice systems. Specifically, in magic-angle twisted bilayer graphene which is also aligned with a hexagonal boron nitride (hBN) cladding layer, we observe a giant anomalous Hall effect as large as 10.4 kΩ, and signs of chiral edge states. This all occurs at zero magnetic field, in a narrow density range around an apparent insulating state at 3 electrons (1 hole) per moiré cell in the conduction miniband [1]. Remarkably, the magnetization of the sample can be reversed by applying a small DC current. Although the anomalous Hall resistance is not quantized, and dissipation is significant, we suggest that the system is essentially a "Chern insulator", a type of topological insulator similar to an integer quantum Hall state. In a quite different superlattice system, ABC-trilayer graphene aligned with hBN, again near 3 electrons (1 hole) per moiré cell a Chern insulator emerges [2]. This time the flat band is a valence miniband, and a magnetic field of order 100 mT is needed to quantize the anomalous hall signal. This trilayer system can be tuned in-situ to display superconductivity instead of magnetism [3]. We will discuss possible magnetic states, complementary probes to examine which state actually emerges as the ground state in each system, and what one might do with such states.

[1] A.L. Sharpe et al., “Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene”, Science 365, 6453 (2019).
[2] G. Chen et al., “Tunable Correlated Chern Insulator and Ferromagnetism in Trilayer Graphene/Boron Nitride Moire Superlattice”, Nature 579, 56 (2020)
[3] G. Chen et al., “Signatures of tunable superconductivity in a trilayer graphene moiré superlattice”, Nature 572, 215 (2019).

What factors drive the growth and decay of a pandemic? Can a study of community differences (in demographics, settlement, mobility, weather, and epidemic history) allow these factors to be identified? Has “herd immunity” to COVID-19 been reached anywhere? What are the best steps to manage/avoid future outbreaks in each community?  We analyzed the entire set of local COVID-19 epidemics in the United States; a broad selection of demographic, population density, climate factors, and local mobility data, in order to address these questions. What we found will surprise you! (based on arXiv:2007.00159)

We propose a reinforcement learning (RL) scheme for feedback quantum control within the quantum approximate optimization algorithm (QAOA). QAOA requires a variational minimization for states constructed by applying a sequence of unitary operators, depending on parameters living in a highly dimensional space. We reformulate such a minimum search as a learning task, where a RL agent chooses the control parameters for the unitaries, given partial information on the system. We show that our RL scheme learns a policy converging to the optimal adiabatic solution for QAOA found by Mbeng et al. arXiv:1906.08948 for the translationally invariant quantum Ising chain. In presence of disorder, we show that our RL scheme allows the training part to be performed on small samples, and transferred successfully on larger systems. Finally, we discuss QAOA on the p-spsin model and how its robustness is enhanced by reinforce learning. Despite the possibility of finding the ground state with polynomial resources even in the presence of a first order phase transition, local optimizations in the p-spsin model suffer from the presence of many minima in the energy landscape. RL helps to find regular solutions that can be generalized to larger systems and make the optimization less sensitive to noise.

References

https://arxiv.org/abs/2003.07419

https://arxiv.org/abs/2004.12323

Many quantum information protocols require the implementation of random unitaries. Because it takes exponential resources to produce Haar-random unitaries drawn from the full n-qubit group, one often resorts to t-designs. Unitary t-designs mimic the Haar-measure up to t-th moments. It is known that Clifford operations can implement at most 3-designs. In this work, we quantify the non-Clifford resources required to break this barrier. We find that it suffices to inject O(t^4 log^2(t) log(1/ε)) many non-Clifford gates into a polynomial-depth random Clifford circuit to obtain an ε-approximate t-design. Strikingly, the number of non-Clifford gates required is independent of the system size – asymptotically, the density of non-Clifford gates is allowed to tend to zero. We also derive novel bounds on the convergence time of random Clifford circuits to the t-th moment of the uniform distribution on the Clifford group. Our proofs exploit a recently developed variant of Schur-Weyl duality for the Clifford group, as well as bounds on restricted spectral gaps of averaging operators. Joint work with J. Haferkamp, F. Montealegre-Mora, M. Heinrich, J. Eisert, and D. Gross.

Given the large push by academia and industry (e.g., IBM and Google), quantum computers with hundred(s) of qubits are at the brink of existence with the promise of outperforming any classical computer. Demonstration of computational advantages of noisy near-term quantum computers over classical computers is an imperative near-term goal. The foremost candidate task for showing this is Random Circuit Sampling (RCS), which is the task of sampling from the output distribution of a random circuit. This is exactly the task that recently Google experimentally performed on 53-qubits.

Stockmeyer's theorem implies that efficient sampling allows for estimation of probability amplitudes. Therefore, hardness of probability estimation implies hardness of sampling. We prove that estimating probabilities to within small errors is #P-hard on average (i.e. for random circuits), and put the results in the context of previous works.

Some ingredients that are developed to make this proof possible are construction of the Cayley path as a rational function valued unitary path that interpolate between two arbitrary unitaries, an extension of Berlekamp-Welch algorithm that efficiently and exactly interpolates rational functions, and construction of probability distributions over unitaries that are arbitrarily close to the Haar measure.