Estimating the dissipation, or the entropy-production rate (EPR), can provide insights into the underlying mechanisms of nonequilibrium-driven processes. However, in practical experimental settings, precise quantification of the EPR can be challenging, as only partial information is typically accessible. Here, we explore the relationship between the observed information and the accuracy of EPR estimation. We employ a range of coarse-grained time-series trajectory data, simulating scenarios where varying degrees of information are available. We discover a hierarchy of lower bounds on the total EPR, demonstrating that an increasing amount of information can be leveraged for obtaining tighter EPR estimation, underscoring the critical role of exploiting the available data. Moreover, we introduce a technique for utilizing waiting times within hidden states and tightening the lower bound on the total EPR for some cases. This approach highlights the potential of hidden features within the data to provide valuable insights into the dissipative dynamics of complex systems.

The classical causal relations between a set of variables, some observed and some latent, can induce both equality constraints (typically conditional independencies) as well as inequality constraints (Instrumental and Bell inequalities being prototypical examples) on their compatible distribution over the observed variables. Enumerating a causal structure's implied inequality constraints is generally far more difficult than enumerating its equalities. Furthermore, only inequality constraints ever admit violation by quantum correlations. For both those reasons, it is important to classify causal scenarios into those which impose inequality constraints versus those which do not. Here we develop methods for detecting such scenarios by appealing to $d$ separation, $e$ separation, and incompatible supports. Many (perhaps all?) scenarios with exclusively equality constraints can be detected via a condition articulated by Henson, Lal, and Pusey (HLP). Considering all scenarios with up to four observed variables, which number in the thousands, we are able to resolve all but three causal scenarios, providing evidence that the HLP condition is, in fact, exhaustive.

Exploiting quantum mechanics for sensing offers unprecedented possibilities. State-of-the-art proposals for novel quantum sensors often rely on the creation of large superpositions and generally detect a field. However, what is the optimal superposition size for detecting an incident particle from a specific direction? This question is nontrivial as, in general, this incident particle will scatter off with varied momenta, imparting varied recoils to the sensor, resulting in decoherence rather than a well-defined measurable phase. By considering scattering interactions of directional particulate environments with a system in a quantum superposition, we find that there is an optimal superposition size for measuring particles via a relative phase. As a consequence of the anisotropy of the environment, we observe a feature in the limiting behavior of the real and imaginary parts of the system's density matrix, linking the optimality of the superposition size to the wavelength of the scatterer.

Modern computational techniques that use a combination of electronic structure calculations, adaptive genetic algorithms, and machine learning data analysis have been recently predicting many new unknown structures that may exhibit desired physical properties. Yet, most of these theoretically discovered structures belong to the realm of virtual phase space, and the great challenge to experimentally observe them still remains. Based on the example of the C36 Laves phase in a Co-Fe-Ta system, we demonstrate a practical route to design and produce a material with desired properties.

To store quantum information, quantum memory plays a central intermediate ingredient in a network. The minimal criterion for a reliable quantum memory is the maintenance of the entangled state, which can be described by the non-entanglement-breaking (non-EB) channel. In this work, we show that all single-qubit quantum memory can be quantified without trusting input state generation. In other words, we provide a semi-device-independent approach to quantify all single-qubit quantum memory. More specifically, we apply the concept of the two-qubit quantum steering ellipsoids to a single-qubit quantum channel and define the channel ellipsoids. An ellipsoid can be constructed by visualizing finite output states within the Bloch sphere. Since the Choi-Jamiołkowski state of a channel can all be reconstructed from geometric data of the channel ellipsoid, a reliable quantum memory can be detected. Finally, we visually quantify the single-qubit quantum memory by observing the volume of the channel ellipsoid.

Magnetic frustration can lead to peculiar magnetic orderings that break a discrete symmetry of the lattice in addition to the fundamental magnetic symmetries (i.e., spin rotation invariance and time-reversal symmetry). In this work, we focus on frustrated quantum magnets and study the nature of the quantum phase transition between a paramagnet and a magnetically ordered state with broken threefold (${\mathbb{Z}}_3$) crystal rotation symmetry. We show that the transition can occur in two stages, giving rise to an intermediate nematic phase in which rotation symmetry is broken but the system remains magnetically disordered. Since the nematic transition is described by the three-state Potts model, the intermediate phase is a ${\mathbb{Z}}_3$ Potts-nematic phase. Our prediction of the existence of a Potts-nematic phase is based on an analysis of bound states formed from two-magnon excitations in the paramagnet, which become gapless while single-magnon excitations remain gapped. By considering three different lattice models, we demonstrate a generic instability towards two-magnon bound state formation in the Potts-nematic channel. We present both numerical results and a general analytical perturbative formula for the bound state binding energy similar to BCS theory. We further discuss a number of different materials that realize key features of the model considered, and thus provide promising venues for possible experimental observation.

We develop a full microscopic theory for a nonlinear phase space filling (NPSF) in strongly coupled two-dimensional polaritonic lattices. Ubiquitous in polaritonic experiments, the theoretical description of NPSF, also known as nonlinear optical saturation, remains limited to perturbative treatment and homogeneous samples. In this study, we go beyond the existing theoretical description and discover the broad scope of regimes where NPSF crucially modifies the optical response. Studying the quantum effects of non-bosonicity, cooperative light-matter coupling, and Coulomb blockade, we reveal several regimes for observing the nonlinear Rabi splitting quench due to the phase space filling. Unlike prior studies, we derive nonlinear Rabi frequency scaling all the way to the saturation limit and show that the presence of a lattice potential leads to qualitatively distinct nonlinearity. We concentrate on the three regimes of NPSF: (1) planar; (2) fractured; and (3) ultralocalized. For the planar saturation, the Rabi frequency decreases exponentially as a function of exciton density. For the fractured case, where excitons form a lattice with sites exceeding the exciton size, we discover fast NPSF at low occupations. This is followed by slower NPSF as the medium becomes fully saturated. This behavior is particularly pronounced in the presence of Coulomb (or Rydberg) blockade, where regions of fast and slow NPSF depend on the strength of repulsion. For the ultralocalized NPSF, we observe the square-root saturation typical to the collection of two-level systems. Our findings shed light on recent observations of strong nonlinearity in heterobilayers of transition metal dichalcogenides where moiré lattices emerge naturally [Nature (London) 591, 61 (2021)]. Finally, the developed theory opens the prospects for engineering strongly nonlinear responses of polaritonic lattices with patterned samples, driving polaritonics into the quantum regime.

We study a driven system in which interaction between particles causes their directional, coupled movement. In that model system, two particles move alternatingly in time on two coupled chains. Without interaction, both particles diffuse along their respective chains, independent from one another. Interaction between them, whether attractive or repellent, leads to an energetic separation of configurations where the particles are close to each other and those where they are farther separated. The energy difference causes close-by particles to remain bound together, forming a doublon. Their relative position in the starting configuration determines whether the doublon moves to the left or right or remains stationary due to the periodic driving.

We provide a non-unit-disk framework to solve combinatorial optimization problems such as maximum cut and maximum independent set on a Rydberg quantum annealer. Our setup consists of a many-body interacting Rydberg system where locally controllable light shifts are applied to individual qubits in order to map the graph problem onto the Ising spin model. Exploiting the flexibility that optical tweezers offer in terms of spatial arrangement, our numerical simulations implement the local-detuning protocol while globally driving the Rydberg annealer to the desired many-body ground state, which is also the solution to the optimization problem. Using optimal control methods, these solutions are obtained for prototype graphs with varying sizes at timescales well within the system lifetime and with approximation ratios close to one. The nonblockade approach facilitates the encoding of graph problems with specific topologies that can be realized in two-dimensional Rydberg configurations and is applicable to both unweighted as well as weighted graphs. A comparative analysis with fast simulated annealing is provided which highlights the advantages of our scheme in terms of system size, hardness of the graph, and the number of iterations required to converge to the solution.

In the field of ergodicity-breaking phases, it has been recognized that quantum avalanches can destabilize many-body localization at a wide range of disorder strengths. This has in particular been demonstrated by the numerical study of a toy model, sometimes simply called the “avalanche model” or the “quantum sun model” [Phys. Rev. Lett. 129, 060602 (2022)], which consists of an ergodic seed coupled to a perfectly localized material. In this paper, we connect this toy model to a well-studied model in random matrix theory, the ultrametric ensemble. We conjecture that the models share the following features. (1) The location of the critical point may be predicted sharply by analytics. (2) On the localized site, both models exhibit Fock space localization. (3) There is a manifold of critical points. On the critical manifold, the eigenvectors exhibit nontrivial multifractal behavior that can be tuned by moving on the manifold. (4) The spectral statistics at criticality is intermediate between Poisson statistics and random matrix statistics, also tunable on the critical manifold. We confirm numerically these properties.

We propose an integrated nonlinear superconducting device based on a nanoelectromechanical shuttle. The system can be described as a qubit coupled to a bosonic mode. The topology of the circuit gives rise to an adjustable qubit-mechanical coupling, allowing the experimenter to tune between linear and quadratic coupling in the mechanical degrees of freedom. Owing to its flexibility and potential scalability, the proposed setup represents an important step towards the implementation of bosonic error correction with mechanical elements in large-scale superconducting circuits. We give preliminary evidence of this possibility by discussing a simple state-swapping protocol that uses this device as a quantum memory element.

Run-and-tumble is a basic model of persistent motion and a motility strategy widespread in micro-organisms and individual cells. In many natural settings, movement occurs in the presence of confinement. While accumulation at the surface has been extensively studied, the transport parallel to the boundary has received less attention. We consider a run-and-tumble particle confined inside a slit, where motion in the bulk alternates with intermittent sojourns at the wall. We first propose a discrete-direction model that is fully tractable and obtain the exact diffusion coefficient characterizing the long-time exploration of the slit. We then use numerical simulations to show that with an adequate choice of parameters, our analytical prediction provides a useful approximation for the diffusion coefficient of run-and-tumble with continuous direction. Finally, we identify the conditions that maximize diffusion within the slit and discuss the optimal mean run time. For swimming bacteria, we find that the optimum is typically reached when the mean run length is comparable to the confinement size.

Complex lifeforms host microbiota, microbes that live synergistically with their host. Accordingly, hosts have mechanisms to defend against and tolerate the microbiota. The intestinal mucus, where these systems collide, plays a pivotal role in managing this relationship, yet lacks an integrative theoretical framework. We propose a minimal model to elucidate dynamics at this interface, focusing on the ileum's mucus defense. The model considers the effect of delay in host antimicrobial peptide secretion and how the host can use two different signals, from the bulk microbiota and from segmented filamentous bacteria (SFB), assuming that the SFB anticipate the bulk microbiota. We propose a theory whereby the host can optimize defense by minimizing antimicrobial peptide production and controlling bacterial exposure. Integrating two recent experiments, we show host dynamics are consistent with sensing both bulk and SFB, supporting our “optimal defense” hypothesis. Therefore, we propose that similar mechanisms could prove advantageous to other species and applicable beyond the ileum's mucus barrier.

An important aspect that strongly impacts the experimental feasibility of quantum circuits is the ratio of gate times and typical error time scales. Algorithms with circuit depths that significantly exceed the error time scales will result in faulty quantum states and error correction is inevitable. We present a comparison of the theoretical minimal gate time, i.e., the quantum speed limit (QSL), for realistic two- and multi-qubit gate implementations in neutral atoms and superconducting qubits. Subsequent to finding the QSLs for individual gates by means of optimal control theory we use them to quantify the circuit QSL of the quantum Fourier transform and the quantum approximate optimization algorithm. In particular, we analyze these quantum algorithms in terms of circuit run times and gate counts both in the standard gate model and the parity mapping. We find that neutral atom and superconducting qubit platforms show comparable weighted circuit QSLs with respect to the system size.

Time-distributed optical feedback in semiconductor lasers has gained attention for its ability to produce high-quality chaos and effectively suppress the time delay signature. However, the fundamental impact of the distribution of feedback in time on laser dynamics remains unexplored. In this paper, we investigate this topic by using fiber Bragg grating (FBG) feedback. We theoretically study the laser response using FBGs of different lengths but similar reflectivity, effectively stretching the impulse response over a longer period while maintaining its overall shape. We observe that there is a critical value of a grating length where fluctuations in laser stability emerge. We attribute this phenomenon to the damping of relaxation oscillations when the zeros of the FBG reflectivity spectrum align with the laser side lobes around the relaxation oscillation frequency. We also uncover an asymmetrical dynamical behavior of the laser for positive and negative frequency detuning. We deduce that this asymmetry is a characteristic feature of FBG feedback and delve into the specificities that trigger such behavior.