Networks of coupled Kerr parametric oscillators (KPOs) are a leading physical platform for analog solving of complex optimization problems. These systems are colloquially known as “Ising machines.” We experimentally and theoretically study such a network under the influence of an external force. The force breaks the collective phase-parity symmetry of the system and competes with the intrinsic coupling in ordering the network configuration, similar to how a magnetic field biases an interacting spin ensemble. Specifically, we demonstrate how the force can be used to control the system, and highlight the crucial role of the phase and symmetry of the force. Our Letter thereby provides a method to create Ising machines with arbitrary bias, extending even to exotic cases that are impossible to engineer in real spin systems.

In the classical regime, thermodynamic state transformations are governed by the free energy. This is also called as the second law of thermodynamics. Previous works showed that, access to a catalytic system allows us to restore the second law in the quantum regime when we ignore coherence. However, in the quantum regime, coherence and free energy are two independent resources. Therefore, coherence places additional nontrivial restrictions on the state transformations that remain elusive. In order to close this gap, we isolate and study the nature of coherence, i.e., we assume access to a source of free energy. We show that allowing catalysis along with a source of free energy allows us to amplify any quantum coherence present in the quantum state arbitrarily. Additionally, any correlations between the system and the catalyst can be suppressed arbitrarily. Therefore, our results provide a key step in formulating a fully general law of quantum thermodynamics.

Uncertainty relations are a fundamental feature of quantum mechanics. How can these relations be found systematically? Here, we develop a semidefinite programming hierarchy for additive uncertainty relations in the variances of noncommuting observables. Our hierarchy is built on the state polynomial optimization framework, also known as scalar extension. The hierarchy is complete in the sense that it converges to tight uncertainty relations. We improve upon upper bounds for all 1292 additive uncertainty relations on up to nine operators for which a tight bound is not known. The bounds are dimension-free and depend entirely on the algebraic relations among the operators. The techniques apply to a range of scenarios, including Pauli, Heisenberg-Weyl, and fermionic operators, and generalize to higher order moments and multiplicative uncertainty relations.

Approaching the long-time dynamics of non-Markovian open quantum systems presents a challenging task if the bath is strongly coupled. Recent proposals address this problem through a representation of the so-called process tensor in terms of a tensor network. We show that for Gaussian environments highly efficient contraction to a matrix product operator (MPO) form can be achieved with infinite MPO evolution methods, leading to significant computational speed-up over existing proposals. The result structurally resembles open system evolution with carefully designed auxiliary degrees of freedom, as in hierarchical or pseudomode methods. Here, however, these degrees of freedom are generated automatically by the MPO evolution algorithm. Moreover, the semigroup form of the resulting propagator enables us to explore steady-state physics, such as phase transitions.

Correlations of fluctuations are essential to understanding many-body systems and key information for advancing quantum technologies. To fully describe the dynamics of a physical system, all time-ordered correlations (TOCs), i.e., the dynamics-complete set of correlations are needed. The current measurement techniques can only access a limited set of TOCs, and there has been no systematic and feasible solution for extracting the dynamic-complete set of correlations hitherto. Here we propose a platform-universal protocol to selectively detect arbitrary types of TOCs via quantum channels. In our method, the quantum channels are synthesized with various controls, and engineer the evolution of a sensor-target system along a specific path that corresponds to a desired correlation. Using nuclear magnetic resonance, we experimentally demonstrate this protocol by detecting a specific type of fourth-order TOC that has never been accessed previously. We also show that the knowledge of the TOCs can be used to significantly improve the precision of quantum optimal control. Our method provides a new toolbox for characterizing the quantum many-body states and quantum noise, and hence for advancing the fields of quantum sensing and quantum computing.

The near equality of the dark matter and baryon energy densities is a remarkable coincidence, especially when one realizes that the baryon mass is exponentially sensitive to UV parameters in the form of dimensional transmutation. We explore a new dynamical mechanism, where in the presence of an arbitrary number density of baryons and dark matter, a scalar adjusts the masses of dark matter and baryons until the two energy densities are comparable. In this manner, the coincidence is explained regardless of the microscopic identity of dark matter and how it was produced. This new scalar causes a variety of experimental effects such as a new force and a (dark) matter density-dependent proton mass.

Auger electron spectroscopy is an omnipresent experimental tool in many fields of fundamental research and applied science. The determination of the kinetic energies of the Auger electrons yields information about the element emitting the electron and its chemical environment at the time of emission. Here, we present an experimental approach to determine Auger spectra for emitter sites in the vicinity of a positive elementary charge based on electron-electron-electron and electron-electron-photon coincidence spectroscopy. We observe a characteristic redshift of the Auger spectrum caused by the Coulomb interaction with the charged environment. Our results are relevant for the interpretation of Auger spectra of extended systems like large molecules, clusters, liquids, and solids, in particular in high-intensity radiation fields which are nowadays routinely available, e.g., at x-ray free-electron laser facilities. The effect has been widely ignored in the literature so far, and some interpretations of Auger spectra from clusters might need to be revisited.

We derive analytically for the first time the downstream evolution of the boundary layer thickness and the friction velocity of the zero-pressure-gradient turbulent boundary layer (ZPGTBL). Lie groups were used to derive the downstream evolution and to obtain the full set of the similarity variables and the leading-order similarity equations. An approximate leading-order solution was obtained using matched asymptotic expansions. The similarities and differences between ZPGTBL and turbulent channel flows in terms of the similarity equations are discussed to support the notion of leading-order universality of the near-wall layer.

Many eukaryotic microorganisms propelled by multiple flagella can swim very rapidly with distinct gaits. Here, we model a three-dimensional mutiflagellate swimmer, resembling the microalgae. When the flagella are actuated synchronously, the swimming efficiency can be enhanced or reduced by interflagella hydrodynamic interactions (HIs), determined by the intrinsic tilting angle of the flagella. The asynchronous gait with a phase difference between neighboring flagella can reduce oscillatory motion via the basal mechanical coupling. In the presence of a spherical body, simulations taking into account the flagella-body interactions reveal the advantage of anterior configuration compared with posterior configuration, where in the latter case an optimal flagella number arises. Apart from understanding the role of HIs in the multiflagellate microorganisms, this work could also guide laboratory fabrications of novel microswimmers.

We develop a practical machine learning approach to determine the disorder landscape of Majorana nanowires by using training of the conductance matrix and inverting the conductance data in order to obtain the disorder details in the system. The inversion carried out through machine learning using different disorder parametrizations turns out to be unique in the sense that any input tunnel conductance as a function of chemical potential and Zeeman energy can indeed be inverted to provide the correct disorder landscape. Our work opens up a qualitatively new direction of directly determining the topological invariant and the Majorana wave-function structure corresponding to a transport profile of a device using simulations that quantitatively match the specific conductance profile. In addition, this also opens up the possibility for optimizing Majorana systems by figuring out the (generally unknown) underlying disorder only through the conductance data. An accurate estimate of the applicable spin-orbit coupling in the system can also be obtained within the same scheme.

One of the central tasks in many-body physics is the determination of phase diagrams. However, mapping out a phase diagram generally requires a great deal of human intuition and understanding. To automate this process, one can frame it as a classification task. Typically, classification problems are tackled using discriminative classifiers that explicitly model the probability of the labels for a given sample. Here we show that phase-classification problems are naturally suitable to be solved using generative classifiers based on probabilistic models of the measurement statistics underlying the physical system. Such a generative approach benefits from modeling concepts native to the realm of statistical and quantum physics, as well as recent advances in machine learning. This leads to a powerful framework for the autonomous determination of phase diagrams with little to no human supervision that we showcase in applications to classical equilibrium systems and quantum ground states.

We study geometries occurring in Feynman integrals that contribute to the scattering of black holes in the post-Minkowskian (PM) expansion. These geometries become relevant to gravitational-wave production from binary mergers through the classical conservative potential. At 4PM, a $K3$ surface is known to occur in a three-loop integral, leading to elliptic integrals in the result. In this Letter, we identify a Calabi-Yau threefold in a four-loop integral, contributing at 5PM. The presence of this Calabi-Yau geometry indicates that completely new functions occur in the full analytical results.

We present laboratory measurements showing the two-dimensional (2D) structure of energy conversion during magnetic reconnection with a guide field over the electron and ion diffusion regions, resolving the separate energy deposition on electrons and ions. We find that the electrons are energized by the parallel electric field at two locations, at the $X$ line and around the separatrices. On the other hand, the ions are energized ballistically by the perpendicular electric field in the vicinity of the high-density separatrices. An energy balance calculation by evaluating the terms of the Poynting theorem shows that 40% of the magnetic energy is converted to particle energy, $2/3$ of which is transferred to ions and $1/3$ to electrons. Further analysis suggests that the energy deposited on particles manifests mostly in the form of thermal kinetic energy in the diffusion regions.

The dielectric response of liquids reflects both reorientation of single molecular dipoles and collective modes, i.e., dipolar cross-correlations. A recent theory predicts the latter to produce an additional slow peak in the dielectric loss spectrum. Following this idea we argue that in supercooled liquids the high-frequency power law exponent of the dielectric loss $\beta$ should be correlated with the degree of dipolar order, i.e., the Kirkwood correlation factor $g_{\mathrm{K}}$. This notion is confirmed for 25 supercooled liquids. While our findings support recent theoretical work the results are shown to violate the earlier Kivelson-Madden theory.

Coexisting orders are key features of strongly correlated materials and underlie many intriguing phenomena from unconventional superconductivity to topological orders. Here, we report the coexistence of two interacting charge-density-wave (CDW) orders in ${\mathrm{EuTe}}_4$, a layered crystal that has drawn considerable attention owing to its anomalous thermal hysteresis and a semiconducting CDW state despite the absence of perfect Fermi surface nesting. By accessing unoccupied conduction bands with time- and angle-resolved photoemission measurements, we find that monolayers and bilayers of Te in the unit cell host different CDWs that are associated with distinct energy gaps. The two gaps display dichotomous evolutions following photoexcitation, where the larger bilayer CDW gap exhibits less renormalization and faster recovery. Surprisingly, the CDW in the Te monolayer displays an additional momentum-dependent gap renormalization that cannot be captured by density-functional theory calculations. This phenomenon is attributed to interlayer interactions between the two CDW orders, which account for the semiconducting nature of the equilibrium state. Our findings not only offer microscopic insights into the correlated ground state of ${\mathrm{EuTe}}_4$ but also provide a general nonequilibrium approach to understand coexisting, layer-dependent orders in a complex system.