We present a theoretical investigation of the chromatic dynamics of the witness beam within a plasma based accelerator. Our approach allows us to include the impact the longitudinal dynamics have on the transverse dynamics. We start by deriving the single particle motion of an electron in an ion column within a nonlinear, blowout wake including adiabatic dampening and adiabatic variations in plasma density. Using this, we calculate the evolution of the beam moments and emittance for an electron beam. Our model can handle near arbitrary longitudinal phase space distributions. We include the effects of energy change in the beam, imperfect wake loading, initial transverse offsets of the beam, and mismatch between the beam and plasma. We use our model to derive analytic saturation lengths for the projected, longitudinal slice, and energy slice emittance under different beam loading conditions. Further, we show that the centroid oscillations and spot sizes vary between the slices and the variation depends strongly on the beam loading. Next, we show how a beam evolves in a full plasma source with density ramps and show that the integral of the plasma density along the ramp determines the impact on the beam. Finally, we derive several simple scaling laws that show how to design a plasma based injector to produce a target beam energy and energy spread.

Connecting superconducting qubits to optical fiber necessitates the conversion of microwave photons to optical photons. Modern experimental demonstrations exhibit strong coupling between a microwave resonator and an optical cavity mediated through phononic modes in a mechanical oscillator. This paradigmatic transduction experiment is bounded by a theoretical efficiency with constant driving amplitudes on electromagnetic resonators. By adding a parametric drive to the microwave resonator and optical cavity, we discover the converted signal through the quantum transducer is amplified, while maintaining a lower level of the added noise. We propose a theoretical framework for time-dependent control of the driving lasers based on the input-output formalism of quantum optics and solve analytically the transduction efficiency and added noise when the control signals parametrically drive the system. Our results show better transduction efficiency and lower added noise in varying parameter regimes relevant to current transduction experiments.

One of the most prominent tasks of machine learning (ML) methods within the field of condensed matter physics has been to classify phases of matter. Given their many successes in performing this task, one may ask whether these methods—particularly unsupervised ones—can go beyond learning the thermodynamic behavior of a system. This question is especially intriguing when considering systems that have a “hidden order”. In this work we study two random spin systems with a hidden ferromagnetic order that can be exposed by applying a Mattis gauge transformation. We demonstrate that the principal component analysis, perhaps the simplest unsupervised ML method, can detect the hidden order, quantify the corresponding gauge variables, and map the original random models onto simpler gauge-transformed ferromagnetic ones, all without any prior knowledge of the underlying gauge transformation. Our work illustrates that ML algorithms can in principle identify not manifestly obvious symmetries of a system.

We present an approach to partitioning network nodes into nonoverlapping communities, a key step in revealing network modularity and functional organization. Our methodology, applicable to networks with weighted or unweighted symmetric edges, uses random walks to explore neighboring nodes in the same community. The walk-likelihood algorithm (WLA) produces an optimal partition of network nodes into a given number of communities. The walk-likelihood community finder employs WLA to predict both the optimal number of communities and the corresponding network partition. We have extensively benchmarked both algorithms, finding that they outperform or match other methods in terms of the modularity of predicted partitions and the number of links between communities. Making use of the computational efficiency of our approach, we investigated a large-scale map of roads and intersections in the state of Colorado. Our clustering yielded geographically sensible boundaries between neighboring communities.

We investigate experimentally the capacitive coupling between a two-electron singlet-triplet spin qubit and flying electrons propagating in quantum Hall edge channels. After calibration of the spin qubit detector, we assess its charge sensibility and demonstrate experimentally the detection of less than five flying electrons with average measurement. This experiment demonstrates that the spin qubit is an ultrasensitive and fast charge detector with the perspective of a future single-shot-detection of a single flying electron. This work opens the route toward quantum electron optics experiments at the single-electron level in semiconductor circuits.

Independent of specific local features, global spatiotemporal structures in diverse phenomena around bifurcation points are described by the complex Ginzburg-Landau equation (CGLE) derived using the reductive perturbation method, which includes prediction of spatiotemporal chaos. The generality in the CGLE scheme includes oscillatory instability in slip behavior between stable and unstable regimes. Such slip transitions accompanying spatiotemporal chaos is expected for frictional interfaces of a thin elastic layer made of soft solids, such as rubber or gel, where especially chaotic behavior may be easily discovered due to their compliance. Slow earthquakes observed in the aseismic-to-seismogenic transition zone along a subducting plate are also potential candidates. This article focuses on the common properties of slip oscillatory instability from the viewpoint of a CGLE approach by introducing a drastically simplified model of an elastic body with a thin layer, whose local expression in space and time allows us to employ conventional reduction methods. Special attention is paid to incorporate a rate-and-state friction law supported by microscopic mechanisms beyond the Coulomb friction law. We discuss similarities and discrepancies in the oscillatory instability observed or predicted in soft matter or a slow earthquake.

Uniformly sampling quantum density matrices has been demonstrated for a long time [Mezzadri, Notices AMS 54, 592 (2007), Życzkowski, J. Math. Phys. 52, 062201 (2011)] and is a valuable tool in the analysis and testing of quantum relations (e.g., the tightness of an uncertainty relation); in ranking the performance of various tools to witness entanglement, nonlocality, discord, etc.; and in probing the geometry of fundamental quantum properties (e.g, the boundary between separable and entangled states). While uniformly sampling quantum states has been shown to be quite valuable, there is to our knowledge no such method to sample these states uniformly at a constant amount of mixedness. This challenge becomes increasingly acute as post-selecting a subensemble of states within a narrow range of, say, purities from this fully uniform sampling becomes overwhelmingly inefficient at high dimension. In this work, we demonstrate how to analytically construct the distribution of density matrices at constant purity (the trace of the square of a density matrix) as our mixedness measure. With this technique at our disposal: we provide analytic formulas for the cumulative radial distribution functions for the uniform distribution of density matrices at constant purity for arbitrary total dimension $N$, with closed form expressions up to $N=4$, and perform numerical integration to analyze the statistics of these uniform-purity distributions at higher dimensions (up to $N=100$). Moreover, we use our new capabilities to: compare different measures of entanglement and nonclassicality, including Wootter's concurrence, the logarithmic negativity and quantum discord, as a function of purity at dimension $N=4$ (two qubits); to find the probability distribution of purities of marginal density matrices from a uniform distribution of joint pure states (and thus the entanglement statistics of this uniform ensemble); and to numerically test a conjectured uncertainty relation between quantum mutual information and the sum of classical mutual informations in complementary bases.

Skyrmions are topological magnetic textures that can arise in noncentrosymmetric ferromagnetic materials. In most systems experimentally investigated to date, skyrmions emerge as classical objects. However, the discovery of skyrmions with nanometer length scales has sparked interest in their quantum properties. Here, we simulate the ground states of two-dimensional spin-$1/2$ Heisenberg lattices with Dzyaloshinskii-Moriya interactions and discover a broad region in the zero-temperature phase diagram which hosts quantum skyrmion lattices. We argue that the quantum skyrmion lattice phase can be detected experimentally in the magnetization profile via local magnetic polarization measurements as well as in the spin structure factor measurable via neutron scattering experiments. Finally, we explore the resulting quantum skyrmion state, analyze its real-space polarization profile and show that it is a nonclassical state featuring entanglement between quasiparticle and environment mainly localized near the boundary spins of the skyrmion.

Controlling the temperature of nanoscale quantum systems is becoming increasingly important in the efforts to develop thermal devices such as quantum heat valves, heat engines, and refrigerators and to explore fundamental concepts in quantum thermodynamics. In practice, however, it is challenging to generate arbitrary time-dependent temperatures, similarly to what has been achieved for electronic voltage pulses. To overcome this problem, we here propose a fully quantum mechanical scheme to control the time-dependent environment temperature of an open quantum system. To this end, we consider a collection of quantum harmonic oscillators that mediate the interactions between the quantum system and a thermal reservoir, and we show how an effective time-dependent temperature can be realized by modulating the oscillator frequencies in time. By doing so, we can apply effective temperature pulses to the quantum system, and it can be cooled below the temperature of the environment. Surprisingly, the scheme can be realized using only a few oscillators, and our proposal thereby paves the way for controlling the temperature of open quantum systems.

Tensor network architectures have emerged recently as a promising approach to various tasks of machine learning, both supervised and unsupervised. In this work we introduce a matrix product state-based network that simultaneously accomplishes the following two tasks: classification (discrimination) and sampling of visual data. We train the network using binary (black and white) version of MNIST, a data set of handwritten digits, to recognize as well as to sample images of a particular digit. We show our trained network is qualitatively representing the indicator function of the “full set” of all possible images of a given format depicting the particular digit. While the notion of the full set is difficult to define from the first principles, our construction provides a working definition, and we show that different ways to build and train the network lead to similar results. We emphasize, this means the trained network learns the “wave function of data,” i.e., can be used to characterize the data itself, providing a novel tool to study global properties of the data sets of interest. First, using quantum mechanical interpretation we characterize the full set by calculating its entanglement entropy. Then we study its geometric properties such as mean Hamming distance, effective dimension, and size. The latter is the total number of images in binary black and white MNIST format which would be recognized as depicting a particular digit. Alternatively, it is the number of images of a given digit one would need to sample before the probability of sampling the same image twice would be of order one. While this number cannot be defined completely rigorously, we show its logarithm is largely independent of the way the network is defined and trained. We find that for different digits this number varies dramatically, from $2^{22}$ for digit 1 to $2^{92}$ for digit 8.

The transition from nucleate to film boiling on micro/nanotextured surfaces is of crucial importance in a number of practical applications, where it needs to be avoided to enable safe and efficient heat transfer. Previous studies have focused on the transition process at the macroscale, where heat transfer and bubble generation are activated on an array of micro/nanostructures. In the present study, we narrow down our investigation scale to a single nanopore, where, through localized Joule heating within the pore volume, single-bubble nucleation and transition are examined at nanosecond resolution using resistive pulse sensing and acoustic sensing. Akin to macroscale boiling, where heterogeneous bubbles can nucleate and coalesce into a film, in the case of nanopores also, patches of heterogeneous bubbles nucleating on the cylindrical pore surface can form a torus-shaped vapor film blanketing the entire pore surface. In contrast to conventional pool boiling, nanopore boiling involves a reverse transition mechanism, where, with increased heat generation, film boiling reverts to nucleate boiling. With increasing bias voltage across the nanopore, the Joule heat production increases within the pore, leading to destabilization and collapse of the torus-shaped vapor film.

We propose a dynamical imprinting scheme to create nodal lines of torus and lemniscate knots via a Raman process in a dilute spinor Bose-Einstein condensate. We calculate the desired parameters and the necessary spatial profiles of the Raman laser fields that couple a realistic multilevel atomic system, and demonstrate the imprinting results via a numerical calculation. Additionally, we show the capability of our method to adjust the size and the aspect ratio of the knotted nodal lines by tuning the parameters of Raman lasers that propagate along different directions.

The eigennmodes in a non-Hermitian system containing nonreciprocal couplings may exhibit an extreme localization, also known as non-Hermitian skin effect (NHSE), under open boundary conditions. Here, we ex- plore unconventional scenarios where the interplay between multiple asymmetric couplings can cause the NHSE to vanish, unlike in known models with nonreciprocal couplings, where the NHSE vanishes only when the non-Hermiticity is turned off. We derive general conditions for the NHSE in a non-Hermitian superlattice in which the overall eigenmode localization is determined by the geometric mean of the cumulative contributions of all asymmetric coupling segments. In the limit of large unit cells, our results provide a route towards the NHSE caused by asymmetric hopping textures, rather than single asymmetric hoppings. We provide explicit electrical circuit setups for realizing our observations, which also extend to other established platforms such as photonics, mechanics, and optics systems, and quantum circuits.

Clean two-dimensional Dirac systems have received a great deal of attention for being a prime candidate to observe hydrodynamical transport behavior in interacting electronic systems. This is mostly due to recent advances in the preparation of ultrapure samples with sufficiently strong interactions. In this paper we investigate the role of collective modes in the thermoelectric transport properties of those systems. We find that dynamical particle-hole pairs, plasmons, make a sizable contribution to the thermal conductivity. While the increase at the Dirac point is moderate, it becomes large towards larger doping. We suspect that this is a generic feature of ultraclean two-dimensional electronic systems, also applicable to degenerate systems.

We present a method for solving eigenvalue problems on a quantum computer based on spectroscopy. The method works by coupling a “probe” qubit to a set of system simulation qubits and then time evolving both the probe and the system under Hamiltonian dynamics. In this way, we simulate spectroscopy on a quantum computer. We test our method on the IBM quantum hardware for a simple single-spin model and an interacting Kitaev chain model. For the Kitaev chain, we trace out the pseudotopological phase boundary for a two-site model.