We investigate the indistinguishability of single photons retrieved from collective Rydberg excitations in cold atomic ensembles. The Rydberg spin waves are created either by off-resonant two-photon excitation to the Rydberg state or by Rydberg electromagnetically induced transparency. To assess the indistinguishability of the generated single photons, we perform Hong-Ou-Mandel experiments between the single photons and weak coherent states of light. We analyze the indistinguishability as a function of the detection window, and we infer a high value of indistinguishability going from $89\%$ for the full waveform to $98\%$ for small detection windows, for the case of photons generated by off-resonant excitation. In the same way, we also investigate the indistinguishability of single photons generated by Rydberg EIT, showing values lower than those corresponding to single photons generated by off-resonant excitation. These results are relevant for the use of Rydberg atoms as quantum network nodes.

The underlying mechanism behind the metal-to-insulator transition in ${\mathrm{VO}}_2$ is still a topic of intense debate. The two leading theoretical interpretations associate the transition with either electron-lattice or electron-electron correlations. Novel experimental results are required to converge towards one of the two scenarios. Here we report on a temperature-dependent angle-resolved photoelectron study of ${\mathrm{VO}}_2$ thin films across the metal-to-insulator transition. The obtained experimental results are compared to density functional theory calculations. We find an overall energy shift and compression of the electronic band structure across the transition while the overall band topology is conserved. The results demonstrate the importance of electron-electron correlations in establishing the insulating state.

Correctly characterizing state preparation and measurement (SPAM) processes is a necessary step towards building reliable quantum processing units (QPUs). In this work, we discuss the subtleties behind separately measuring SPAM errors. We propose a protocol that can separately estimate SPAM errors, in the case where quantum gates are ideal. In the case where the quantum gates are imperfect, we derive bounds on the estimated SPAM error rates, based on gate error measures, which can be estimated independently of SPAM processes. Our method shows that the gauge ambiguity in characterizing SPAM operations can be resolved by assuming that there exists one qubit whose initial state is uncorrelated with other qubits in a QPU. We test the protocol on a publicly available five-qubit QPU and demonstrate its validity by comparing our results with simulations.

We show how Oshikawa's theorem for the Fermi surface volume of the Kondo lattice can be extended to the $\mathrm{SU}\left(N\right)$ symmetric case. By extending the theorem, we can show that the mechanism of Fermi surface expansion seen in the large $N$ mean-field theory is directly linked to the expansion of the Fermi surface in a spin-$\frac{1}{2}$ Kondo lattice. This linkage enables us to interpret the expansion of the Fermi surface in a Kondo lattice as a fractionalization of the local moments into heavy electrons. Our method allows extension to a pure U(1) spin liquid, where we find the volume of the spinon Fermi surface by applying a spin twist, analogous to Oshikawa's, [Phys. Rev. Lett. 84, 3370 (2000)] flux insertion. Lastly, we discuss the possibility of interpreting the ${\mathrm{FL}}^{*}$ phase characterized by a small Fermi surface in the absence of symmetry breaking, as a nontopological coexistence of such a U(1) spin liquid and an electronic Fermi liquid.

A variant of the susceptible-infected-recovered model for an inhomogeneous population is introduced to account for the effect of variability in susceptibility and infectiousness across a population. An initial formulation of this dynamics leads to infinitely many differential equations. Our model, however, can be reduced to a single first-order one-dimensional differential equation. Using this approach, we provide quantitative solutions for different distributions. In particular, we use GPS data from $\sim {10}^7$ cell phones to determine an empirical distribution of the number of individual contacts and use this to infer a possible distribution of susceptibility and infectivity. We quantify the effect of superspreaders on the early growth rate ${\mathcal{R}}_0$ of the infection and on the final epidemic size, the total number of people who are ever infected. We discuss the features of the distribution that contribute most to the dynamics of the infection.

Recently, hypergraphs have attracted considerable interest from the research community as a generalization of networks capable of encoding higher-order interactions, which commonly appear in both natural and social systems. Epidemic dynamics in hypergraphs has been studied by using the simplicial susceptible-infected-susceptible ($s$-SIS) model; however, the efficient immunization strategy for epidemics in hypergraphs is not studied despite the importance of the topic in mathematical epidemiology. Here, we propose an immunization strategy that immunizes hyperedges with high simultaneous infection probability (SIP). This strategy can be implemented in general hypergraphs. We also generalize the edge epidemic importance (EI)-based immunization strategy, which is the state of the art in complex networks. However, it does not perform as well as the SIP-based method in hypergraphs despite its high computational cost. We also show that immunizing hyperedges with high H-eigenscore effectively contains the epidemics in uniform hypergraphs. A high SIP of a hyperedge suggests that the hyperedge is a “hotspot” of the epidemic process. Therefore, SIP can be used as a centrality measure to quantify a hyperedge's influence on higher-order dynamics in general hypergraphs. The effectiveness of the immunization strategies suggests the necessity of scientific, data-driven, systematic policy-making for epidemic containment.

Hyperbolic metamaterials have attracted considerable interest in the research community for their peculiar ability to enhance control of electromagnetic waves' propagation. Although conformal transformation optics provides a unique platform for metamaterials design, this method has not been used for hyperbolic metamaterials yet. This comes from the lack of a well-defined mathematical structure. We extend conformal transformation optics to hyperbolic metamaterials, by applying Clifford algebra to analyze light propagation. We will show that the effective line element of a trajectory of light propagation conforms to ultrahyperbolic—not Euclidean—geometry. We also, by using conformal hyperbolic mapping, obtain all conformal spaces with Minkowski space-time. Finally, we employ this theory to study the electric-field pattern of dipoles.

Quantum computations and simulations require strong coherent coupling between qubits, which may be spatially separated. Achieving this coupling for solid-state-based spin qubits is a long-standing challenge. Here we theoretically investigate a method for achieving such a coupling, based on superconducting nanostructures designed to channel the magnetic flux created by the qubits. We detail semiclassical analytical calculations and simulations of the magnetic field created by a magnetic dipole, depicting the spin qubit, positioned directly below nanofabricated apertures in a superconducting layer. We show that such structures could channel the magnetic flux, enhancing the dipole-dipole interaction between spin qubits and changing its scaling with distance, thus potentially paving the way for controllably engineering an interacting spin system.

We demonstrate the design of a matter-wave interferometer to measure acceleration in one dimension with high precision. The system we base this on consists of ultracold atoms in an optical lattice potential created by interfering laser beams. Our approach uses reinforcement learning, a branch of machine learning that generates the protocols needed to realize lattice-based analogs of optical components including a beam splitter, a mirror, and a recombiner. The performance of these components is evaluated by comparison with their optical analogs. The interferometer's sensitivity to acceleration is quantitatively evaluated using a Bayesian statistical approach. We find the sensitivity to surpass that of standard Bragg interferometry, demonstrating the future potential for this design methodology.

We apply deep-neural-network-based techniques to quantum state classification and reconstruction. Our methods demonstrate high classification accuracies and reconstruction fidelities, even in the presence of noise and with little data. Using optical quantum states as examples, we first demonstrate how convolutional neural networks (CNNs) can successfully classify several types of states distorted by, e.g., additive Gaussian noise or photon loss. We further show that a CNN trained on noisy inputs can learn to identify the most important regions in the data, which potentially can reduce the cost of tomography by guiding adaptive data collection. Secondly, we demonstrate reconstruction of quantum-state density matrices using neural networks that incorporate quantum-physics knowledge. The knowledge is implemented as custom neural-network layers that convert outputs from standard feed-forward neural networks to valid descriptions of quantum states. Any standard feed-forward neural-network architecture can be adapted for quantum state tomography (QST) with our method. We present further demonstrations of our proposed QST technique with conditional generative adversarial networks (QST-CGAN) [Ahmed et al., Phys. Rev. Lett. 127, 140502 (2021)]. We motivate our choice of a learnable loss function within an adversarial framework by demonstrating that the QST-CGAN outperforms, across a range of scenarios, generative networks trained with standard loss functions. For pure states with additive or convolutional Gaussian noise, the QST-CGAN is able to adapt to the noise and reconstruct the underlying state. The QST-CGAN reconstructs states using up to two orders of magnitude fewer iterative steps than iterative and accelerated projected-gradient-based maximum-likelihood estimation (MLE) methods. We also demonstrate that the QST-CGAN can reconstruct both pure and mixed states from two orders of magnitude fewer randomly chosen data points than these MLE methods. Our paper opens possibilities to use state-of-the-art deep-learning methods for quantum state classification and reconstruction under various types of noise.

Understanding the critical condition and mechanism of the droplet wetting transition between Cassie-Baxter state and Wenzel state triggered by an external electric field is of considerable importance because of its numerous applications in industry and engineering. However, such a wetting transition on a patterned surface is still not fully understood, e.g., the effects of electrowetting (EW) number, geometry of the patterned surfaces and droplet volume on the transition have not been systematically investigated. In this paper, we propose a theoretical model for the Cassie-Baxter-Wenzel wetting transition triggered by an external voltage applied to a droplet placed on a mirco-pillared surface or a porous substrate. It is found that the external field applied lowers the energy barrier for the droplet to cross over and complete the wetting transition. Our calculations also indicate that for a fixed droplet volume, the critical EW number (voltage) will increase (decrease) along with the surface roughness for a micropillar-patterned (porous) surface, and if the surface roughness is fixed, a small droplet tends to ease the critical EW condition for the transition. Besides, three-dimensional phase diagrams in terms of EW number, surface roughness, and droplet volume are constructed to illustrate the wetting transition. Our theoretical model can be used to explain the previous experimental results about the Cassie-Baxter-Wenzel wetting transition reported in the literature.

Quantum spin-liquid van der Waals magnets such as ${\mathrm{TaS}}_2$, ${\mathrm{TaSe}}_2$, and ${\mathrm{RuCl}}_3$ provide a natural platform to explore new exotic phenomena associated with spinon physics, whose properties can be controlled by exchange proximity with ferromagnetic insulators such as ${\mathrm{CrBr}}_3$. Here we put forward a twisted van der Waals heterostructure based on a quantum spin-liquid bilayer encapsulated between ferromagnetic insulators. We demonstrate the emergence of spinon flat bands and topological spinon states in such heterostructure, where the emergence of a topological gap is driven by the twist. We further show that the spinon band structure can be controlled via exchange proximity effect to the ferromagnetic leads. We finally show how by combining small magnetic fields with tunneling spectroscopy, magnetically encapsulated heterostructures provide a way of characterizing the nature of the quantum spin-liquid state. Our results put forward twisted quantum spin-liquid bilayers as potential platforms for exotic moire spinon phenomena, demonstrating the versatility of magnetic van der Waals heterostructures.

We propose a protocol for bosonic binomial-code nonadiabatic holonomic quantum computation in a system composed of an artificial atom ultrastrongly coupled to a cavity resonator. In our protocol, the binomial codes, formed by superpositions of Fock states, can greatly save physical resources to correct errors in quantum computation. We apply to the system strong driving fields designed by shortcuts-to-adiabatic methods. This reduces the gate time to tens of nanoseconds. Noise induced by control imperfections can be suppressed by a systematic-error-sensitivity nullification method. As a result, this protocol can rapidly $(\sim 35\mathrm{ns})$ generate fault-tolerant and high-fidelity ($\gtrsim 98\%$ with experimentally realistic parameters) quantum gates.

Complex lattices provide a versatile ground for fascinating quantum many-body physics. Here, we propose an exotic mechanics for generating orbital frustration in hexagonal lattices. We study two-component (pseudospin-$\frac{1}{2}$) Bose gases in $p$-orbital bands of two-dimensional hexagonal lattices, and find that the system exhibits previously untouched orbital frustration as a result of the interplay of spin and orbital degrees of freedom, in contrast to normal Ising-type orbital ordering of spinless $p$-orbital band bosons in two-dimensional hexagonal lattices. Based on the classification by symmetry analysis, we find the interplay of orbital frustration and strong interaction leads to exotic Mott and superfluid phases with spin-orbital intertwined orders, in spite of the complete absence of spin-orbital interaction in the Hamiltonian. Our study implies many-body correlations in a multiorbital setting could induce rich spin-orbital intertwined physics in complex lattice structures.

The entropy stabilized oxide ${\mathrm{Mg}}_{0.2}{\mathrm{Co}}_{0.2}{\mathrm{Ni}}_{0.2}{\mathrm{Cu}}_{0.2}{\mathrm{Zn}}_{0.2}\mathrm{O}$ exhibits antiferromagnetic order and magnetic excitations, as revealed by recent neutron scattering experiments. This observation raises the question of the nature of spin-wave excitations in such disordered systems. Here, we investigate theoretically the magnetic ground state and the spin-wave excitations using linear spin-wave theory in combination with the supercell approximation to take into account the extreme disorder in this magnetic system. We find that the experimentally observed antiferromagnetic structure can be stabilized by a rhombohedral distortion together with large second-nearest-neighbor interactions. Our calculations show that the spin-wave spectrum consists of a well-defined low energy coherent spectrum in the background of an incoherent continuum that extends to higher energies.