Hypergolic ignition of a bipropellant is an intrinsically nonpremixed physicochemical process that involves both chemistry and fluidic mixing. While the ignition delay time (IDT) of various hypergolic propellants has been extensively measured by using the prevalent droplet test, the effect of fluidic mixing on the hypergolic ignition process has rarely been studied. Compared with the well-understood droplet mixing within the same liquid, a prominent feature of bipropellant droplet mixing is the substantial surface tension difference, which induces a Marangoni effect upon droplet coalescence; however, it has not been addressed by previous hypergolic ignition studies and still remains inadequately understood. In this work, we numerically study the internal mixing of colliding droplets of different surface tensions with implications for hypergolic propellant ignition. The results show that the Marangoni effect substantially enhances droplet mixing compared with the situation without surface tension difference, and indicate the Marangoni effect could be a pivotal physical mechanism in hypergolic ignition. In particular, we identify an interesting phenomenon in that the Marangoni effect yields a nonmonotonic variation of internal mixing with increasing impact inertia, and this provides a likely interpretation of the nonmonotonic variation of the IDT experimentally observed by Zhang et al. [Combust. Flame 173, 276–287 (2016)]. Although binary droplet collision is employed as the specific object of the study, the present results could also provide insight into the hypergolic ignition of a bipropellant using various mixing methodologies, such as impinging jet and droplet-pool impact.

Microwave loss of a semiconducting nanowire implemented in a cavity electromechanical system enables bolometric-microwave-power measurements at millikelvin temperatures. This hybrid system consists of a superconducting microwave cavity capacitively coupled to a suspended $\mathrm{In}\mathrm{As}$ nanowire. As a constant voltage is applied across a vacuum gap between the nanowire and the bottom electrode, the nanowire resistance embedded in the microwave resonator follows its own mechanical vibration. The mechanically modulated resistance of the nanowire contributes to microwave sidebands exhibiting its mechanical resonance. The presence of this resistive component provides the device with enhanced sensitivity to microwave dissipation. This dissipation localized at the nanowire results in a temperature increase, producing a frequency shift of the mechanical resonance sensitive to the microwave power. We employ a circuit model to demonstrate that semiconducting nanowires provide optimal resistances for the nanomechanical microwave bolometry. Our technique could benefit precision microwave measurements in quantum-device research.

Detecting traveling photons is an essential primitive for many quantum-information processing tasks. We introduce a single-photon detector design operating in the microwave domain, based on a weakly nonlinear metamaterial where the nonlinearity is provided by a large number of Josephson junctions. The combination of weak nonlinearity and large spatial extent circumvents well-known obstacles limiting approaches based on a localized Kerr medium. Using numerical many-body simulations we show that the single-photon detection fidelity increases with the length of the metamaterial to approach one at experimentally realistic lengths. A remarkable feature of the detector is that the metamaterial approach allows for a large detection bandwidth. The detector is nondestructive and the photon population wavepacket is minimally disturbed by the detection. This detector design offers promising possibilities for quantum information processing, quantum optics and metrology in the microwave frequency domain.

Quantum error correction is essential for robust quantum-information processing with noisy devices. As bosonic quantum systems play a role in quantum sensing, communication, and computation, it is useful to design error-correction codes suitable for these systems against various different types of noises. While most efforts aim at protecting qubits encoded into the infinite-dimensional Hilbert space of a bosonic mode, Ref. [Phys. Rev. Lett. 125, 080503 (2020)] proposed an error-correction code to maintain the infinite-dimensional-Hilbert-space nature of bosonic systems by encoding a single bosonic mode into multiple bosonic modes. Enabled by Gottesman-Kitaev-Preskill states as ancilla, the code overcomes the no-go theorem of Gaussian error correction. In this work, we generalize the error-correction code to the scenario with general correlated and heterogeneous Gaussian noises, including memory effects. We introduce Gaussian preprocessing and postprocessing to convert the general noise model to an independent but heterogeneous collection of additive white Gaussian noise channels and then apply concatenated codes in an optimized manner. To evaluate the performance, we develop a theory framework to enable the efficient calculation of the noise SD after the error correction, despite the non-Gaussian nature of the codes. Our code provides the optimal scaling of the residue-noise SD with the number of modes and can be widely applied to distributed sensor networks, network communication, and composite quantum-memory systems.

There is a large gap between theory and practice in quantum key distribution (QKD) because real devices do not satisfy the assumptions required by the security proofs. Here, we close this gap by introducing a simple and practical measurement-device-independent-QKD type of protocol, based on the transmission of coherent light, for which we prove its security against any possible imperfection and/or side channel from the quantum communication part of the QKD devices. Our approach only requires to experimentally characterize an upper bound of one single parameter for each of the pulses sent, which describes the quality of the source. Moreover, unlike device-independent (DI) QKD, it can accommodate information leakage from the users’ laboratories, which is essential to guarantee the security of QKD implementations. In this sense, its security goes beyond that provided by DI QKD, yet it delivers a secret key rate that is various orders of magnitude greater than that of DI QKD.

Quantum sensing and metrology promise useful insights and alternative techniques to surpass the measurement limits of a classical framework. Significant improvement has been made in the areas of imaging, positioning, timing, interferometry, communication, and information processing through quantum detection and estimation techniques. In this Letter, we focus on the application of quantum information for spectral measurements. Specifically, we study the quantum limit to resolve two spectral modes with small frequency separation. We show that frequency superresolution can be achieved with spectrotemporal shaping of input fields before detection. Through a numerical optimization algorithm, we design the apparatus for spectrotemporal shaping based on phase modulation and dispersion engineering. This scheme can achieve performance close to the quantum limit with minimum resources, showing the robustness for experimental implementation and real-world applications.

We develop a type of magnetometer consisting of a hybrid quantum interference device (HyQUID) that is set in a bistable state. We demonstrate its operation in a latching mode that can be employed to measure small changes in the applied flux. The device can be used to probe the flux state of a superconducting circuit using straightforward electrical resistance measurements, making it suitable as a simple qubit readout with low back action.

In this work, we investigate the spin and valley transport properties of a $\mathrm{W}{\mathrm{Se}}_2$ monolayer placed on top of a ferromagnetic insulator. We are interested in controlling the transport properties by applying external potentials to the system. To obtain spin and valley polarizations, we consider a single- and a double-barrier structure with gate potentials. We analyze how the efficiency of these polarized transport properties depends on the gate-potential intensities and geometrical configurations. Additionally, we investigate how the spin and valley transport properties are modified when an ac potential is applied to the system. We obtain a controllable modulation of the spin and valley polarizations as a function of the intensity and frequency of the ac potential, mainly in the terahertz range. These results validate the proposal of double quantum well structures of $\mathrm{W}{\mathrm{Se}}_2$ as candidates to provide spin- and valley-dependent transport within an optimal geometrical parameter regime.

Quantum error correction is vital for implementing universal quantum computing. A key component is the encoding circuit that maps a product state of physical qubits into the encoded multipartite entangled logical state. Known methods are typically not “optimal” either in terms of the circuit depth (and therefore the error burden) or the specifics of the target platform, i.e., the native gates and topology of a system. This work introduces a variational compiler for efficiently finding the encoding circuit of general quantum error-correcting codes with given quantum hardware. Focusing on the noisy intermediate-scale quantum regime, we show how to systematically compile the circuit following an optimizing process seeking to minimize the number of noisy operations that are allowed by the noisy quantum hardware or to obtain the highest fidelity of the encoded state with noisy gates. We demonstrate our method by deriving efficient encoders for logic states of the five-qubit code and the seven-qubit Steane code. We describe ways to augment the discovered circuits with error detection. Our method is applicable quite generally for compiling the encoding circuits of quantum error-correcting codes.

Exploiting the physics of nanoelectronic devices is a major lead for implementing compact, fast, and energy-efficient artificial intelligence. In this work, we propose a strategy in this direction, where assemblies of spintronic resonators used as artificial synapses can classify analogue radio-frequency signals directly without digitalization. The resonators convert the radio-frequency input signals into direct voltages through the spin-diode effect. In the process, they multiply the input signals by a synaptic weight, which depends on their resonance frequency. We demonstrate through physical simulations with parameters extracted from experimental devices that frequency-multiplexed assemblies of resonators implement the cornerstone operation of artificial neural networks, multiply and accumulate (mac), directly on microwave inputs. The results show that, even with a nonideal realistic model, the outputs obtained with our architecture remain comparable to that of a traditional mac operation. Using a conventional machine-learning framework augmented with equations describing the physics of spintronic resonators, we train a single-layer neural network to classify radio-frequency signals encoding 8 × 8 pixel handwritten-digit pictures. The spintronic neural network recognizes the digits with an accuracy of 99.96%, equivalent to purely software neural networks. This mac implementation offers a promising solution for fast low-power radio-frequency classification applications and another building block for spintronic deep neural networks.

Radical pairs and the dynamics they undergo are prevalent in many chemical and biological systems. Specifically, it has been proposed that the radical-pair mechanism results from a relatively strong hyperfine interaction with its intrinsic nuclear spin environment. While the existence of this mechanism is undisputed, the nanoscale details remain to be experimentally shown. Here, we analyze the role of a quantum sensor in detecting the spin dynamics (non-Markovian) of individual radical pairs in the presence of a weak magnetic field. We show how quantum control methods can be used to set apart the dynamics of the radical-pair mechanism at various stages of the evolution. We expect these findings to have implications to the understanding of the physical mechanism in magnetoreception and other biochemical processes with a microscopic detail.

We investigate the tensile stress in freely suspended nanomechanical string resonators, and observe a material-independent dependence on the resonator length. We compare strongly stressed string resonators fabricated from four different material systems based on amorphous silicon nitride, crystalline silicon carbide as well as crystalline indium gallium phosphide. The tensile stress is found to increase by approximately $50$% for shorter resonators. We establish a simple elastic model to describe the observed length dependence of the tensile stress. The model accurately describes our experimental data. This opens a perspective for stress engineering the mechanical quality factor of nanomechanical string resonators.

Simulations of blood flows in microfluidic devices and physiological systems are gaining importance in complementing experimental and clinical studies. The predictive capabilities of these simulations hinge on the parameters of the red blood cell (RBC) model that are usually calibrated from experimental data. However, these parameter values may vary drastically when calibrated using different experimental quantities or experimental settings. In turn, the results of existing blood flow simulations largely depend on the utilized parameters that have been chosen to validate a particular experiment. We suggest a revision to this type of model calibration to properly integrate experimental data in the computational models and accordingly inform their predictions. In this context, we introduce the calibration of a popular RBC model using data-driven, hierarchical Bayesian inference. We employ data from classical experiments of RBC stretching by optical tweezers and tank treading in shear flows, and distinguish the calibration of the model parameters through single-level and hierarchical Bayesian uncertainty quantification. We find that the optimal model parameters depend not only on the data used for the inference but also on the way the data are used in the inference process. Single-level Bayesian models predict well the data used in their calibration, but are inferior to the hierarchical Bayesian model at predicting previously unseen data. This work demonstrates that the proper integration of experimental data is essential for the development of a robust and transferable RBC model. We believe that the present study can serve as a prototype across scientific fields, in revising the integration of computational models and heterogeneous experimental data.

By doping and aging in a ferroelectric, we realize a “reversible domain switching” that produces the desirable double hysteresis loop typical of an antiferroelectric with a small remnant polarization and consequently large storage densities. We use Ginzburg-Landau modeling to demonstrate our concept theoretically, and then our predictions are experimentally validated in ${\mathrm{Ba}\mathrm{Ti}\mathrm{O}}_3$-based single crystals (${\mathrm{K}}^{+}$ doped) and ceramics (${\mathrm{Nb}}^{5+}$ and ${\mathrm{Mn}}^{3+}$ doped), where we measure the enhancement of energy storage due to aging. Based on our experimental results, we estimate that our proposed strategy of doping and aging will result in storage energy density increases of 5 to 35% depending on the ferroelectric system. Thus, our proposed concept can be widely employed across the range of ferroelectric systems. Moreover, as energy dissipation and output efficiency are useful in energy-storage applications, we show how our hybrid doping with acceptor and donor is an efficient way to decrease dissipation and increase output efficiency. In terms of fatigue, we show that even after ${10}^6$ cycles, the double hysteresis loop of the aged acceptor-doped ferroelectric material yields an energy-storage density and efficiency that is quite robust.

We study the interaction of surface acoustic waves (SAWs) with spin waves (SWs) in a ${\mathrm{Co}}_{40}{\mathrm{Fe}}_{40}{\mathrm{B}}_{20}$/$\mathrm{Au}$/${\mathrm{Ni}}_{81}{\mathrm{Fe}}_{19}$ system composed of two ferromagnetic layers separated by a nonmagnetic $\mathrm{Au}$ spacer layer. Because of interlayer magnetic dipolar coupling between the two ferromagnetic layers, a symmetric and an antisymmetric SW mode form, which both show a highly nondegenerate dispersion relation for oppositely propagating SWs. Due to magnetoacoustic SAW-SW interaction, we observe highly nonreciprocal SAW transmission in the piezoelectric-ferromagnetic hybrid device. We experimentally and theoretically characterize the magnetoacoustic wave propagation as a function of frequency, wave vector, and external magnetic field magnitude and orientation. Additionally, we demonstrate that the nonreciprocal SW dispersion of a coupled magnetic bilayer is highly tuneable and not limited to ultrathin magnetic films, in contrast to the nonreciprocity induced by the interfacial Dzyaloshinskii-Moriya interaction. Therefore, magnetoacoustic coupling in ferromagnetic multilayers provides a promising route towards building efficient acoustic isolators.

Optically active spin centers associated with atomic scale defects in $\mathrm{Si}\mathrm{C}$ are promising candidates for quantum technology, owing to their outstanding optical and spin properties. Photoluminescence as a mature optical investigating tool is widely used for the identification of spin defects and exploration of their properties. However, in the case of spectrally overlapping contributions from different types of defects, traditional photoluminescence measurements cannot be used to separately obtain their optical and vibrational properties, such as the local phonon energy and the Debye-Waller factor. Here, we apply spin-resonant microwave-assisted spectroscopy to investigate the optical and vibrational properties of silicon vacancies in 6H-$\mathrm{Si}\mathrm{C}$ and divacancies in 4H- and 6H-$\mathrm{Si}\mathrm{C}$. We isolate contributions from each type of defect, investigate their local vibrational modes, and obtain the Debye-Waller factor. This work proves that microwave-assisted spectroscopy is a suitable tool for the investigation of optical and vibrational properties of a large variety of spin defects.