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At least 631 records · Page 35

Quantum mixed state compiling

The task of learning a quantum circuit to prepare a given mixed state is a fundamental quantum subroutine. We present a variational quantum algorithm (VQA) to learn mixed states which is suitable for near-term hardware. Our algorithm represents a generalization of previous VQAs that aimed at learning preparation circuits for pure states. We consider two different ansätze for compiling the target state; the first is based on learning a purification of the state and the second on representing it as a convex combination of pure states. In both cases, the resources required to store and manipulate the compiled state grow with the rank of the approximation. Thus, by learning a lower rank approximation of the target state, our algorithm provides a means of compressing a state for more efficient processing. As a byproduct of our algorithm, one effectively learns the principal components of the target state, and hence our algorithm further provides a new method for principal component analysis. We investigate the efficacy of our algorithm through extensive numerical implementations, showing that typical random states and thermal states of many body systems may be learnt this way. Additionally, we demonstrate on quantum hardware how our algorithm can be used to study hardware noise-induced states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Diabatic quantum annealing for the frustrated ring model

Abstract Quantum annealing (QA) is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare ground state and a problem Hamiltonian whose ground state encodes solutions to an optimization problem. The standard implementation relies on the evolution being adiabatic: keeping the system in the instantaneous ground state with high probability and requiring a time scale inversely related to the minimum energy gap between the instantaneous ground and excited states. However, adiabatic evolution can lead to evolution times that scale exponentially with the system size, even for computationally simple problems. Here, we study whether non-adiabatic evolutions with optimized annealing schedules can bypass this exponential slowdown for one such class of problems called the frustrated ring model. For sufficiently optimized annealing schedules and system sizes of up to 39 qubits, we provide numerical evidence that we can avoid the exponential slowdown. Our work highlights the potential of highly-controllable QA to circumvent bottlenecks associated with the standard implementation of QA.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Physically motivated analytical expression for the temperature dependence of the zero-field splitting of the nitrogen-vacancy center in diamond

The temperature dependence of the zero-field splitting (ZFS) between the | $m_s$ = 0 $\rangle$ and | $m_s$ = ±1 $\rangle$ levels of the nitrogen-vacancy (NV) center's electronic ground-state spin triplet can be used as a robust nanoscale thermometer in a broad range of environments. However, despite numerous measurements of this dependence in different temperature ranges, to our knowledge no analytical expression has been put forward that captures the scaling of the ZFS of the NV center across all relevant temperatures. Here we present a simple, analytical, and physically motivated expression for the temperature dependence of the NV center's ZFS that matches all experimental observations, in which the ZFS shifts in proportion to the occupation numbers of two representative phonon modes. In contrast to prior models our expression does not diverge outside the regions of fitting. In conclusion, we show that our model quantitatively matches experimental measurements of the ZFS from 15 to 500 K in single NV centers in ultrapure bulk diamond, and we compare our model and measurements to prior models and experimental data.

36 MATERIALS SCIENCE↗

Imaging beyond the surface region: Probing hidden materials via atomic force microscopy

Probing material properties at surfaces down to the single-particle scale of atoms and molecules has been achieved, but high-resolution subsurface imaging remains a nanometrology challenge due to electromagnetic and acoustic dispersion and diffraction. The atomically sharp probe used in scanning probe microscopy (SPM) has broken these limits at surfaces. Subsurface imaging is possible under certain physical, chemical, electrical, and thermal gradients present in the material. Of all the SPM techniques, atomic force microscopy has entertained unique opportunities for nondestructive and label-free measurements. Here, we explore the physics of the subsurface imaging problem and the emerging solutions that offer exceptional potential for visualization. We discuss materials science, electronics, biology, polymer and composite sciences, and emerging quantum sensing and quantum bio-imaging applications. The perspectives and prospects of subsurface techniques are presented to stimulate further work toward enabling noninvasive high spatial and spectral resolution investigation of materials including meta- and quantum materials.

74 ATOMIC AND MOLECULAR PHYSICS↗

Dual-Resonator Kinetic-Inductance Detector for Distinction between Signal and 1/ƒ Frequency Noise

Astronomical kinetic inductance detectors (KIDs), similar to quantum information devices, experience performance-limiting noise from materials. In particular, 1/ƒ (frequency) noise arises from two-level system defects (TLSs) in the circuit dielectrics and material interfaces and can be a dominant noise mechanism. Here, we present a dual-resonator KID (DuRKID), which is designed for improved noise-equivalent power relative to standard 1/ƒ -noise-limited KIDs. In this study we present the DuRKID schematic, a fabricated example, our first measurement results, a theoretical model including 1/ƒ noise, and a system-noise model containing additional noise sources. The circuit consists of two superconducting resonators sharing an electrical capacitance bridge of four capacitors, each of which hosts TLSs. The device is intended to operate using hybridization of the modes, which causes TLSs to either couple to one mode or the other, depending upon which capacitor they reside in. In contrast, the signal will affect a resonator inductance and, due to mode hybridization, this causes correlated frequency changes in both modes. Therefore, one can better distinguish the photon signal from the TLS frequency noise. To achieve hybridization, a TiN inductor is current biased to allow tuning of one bare-resonator mode into degeneracy with the other. Measurements show that the resonator modes hybridize as expected. The inter-resonator coupling and unintentional coupling of the two resonators to transmission lines are also characterized in measurements. A quantum information-science model allows device-parameter extraction from experimental data and a 1/ƒ noise analysis with uncorrelated noise. A system-noise analysis of the DuRKID, with comparisons to standard KIDs, is performed with generation-recombination noise and amplifier noise. The study reveals that the DuRKID can exhibit a large performance advantage over TLS-limited KID detectors.

N Forouzani↗

Large moiré superstructure of stacked incommensurate charge density waves

This article reports how two different charge density waves with slightly different wavevectors can exist in the same crystal and create moiré superstructure. Advances in heterostructure fabrication have opened new frontiers in moiré physics. Here we extend moiré engineering from artificially assembled thin flakes with mismatched lattice parameters to materials that host incommensurate orders, presenting a long-period moiré superlattice in a layered charge-density-wave compound, EuTe 4 . Using high-momentum-resolution X-ray diffraction, we found two coexisting incommensurate charge density waves with slightly mismatched in-plane wavevectors. The interaction between these two charge density waves leads to joint commensuration with the lattice and a moiré superstructure with a period of ~13.6 nm, offering key insights into the unique properties of EuTe4, such as the temperature-invariant incommensurate wavevectors and unconventional in-gap states. Owing to interlayer phase shifts, the moiré superstructure exhibits a clear thermal hysteresis, accounting for the large hysteresis in electrical resistivity and numerous metastable states. Our findings open new directions for moiré engineering based on incommensurate lattices and highlight the important role of interlayer ordering in stacked structures.

36 MATERIALS SCIENCE↗

Advanced Quantum Poisson Solver in the NISQ era

The Poisson equation has many applications across the broad areas of science and engineering. Most quantum algorithms for the Poisson solver presented so far, either suffer from lack of accuracy and/or are limited to very small sizes of the problem, and thus have no practical usage. Here we present an advanced quantum algorithm for solving the Poisson equation with high accuracy and dynamically tunable problem size. After converting the Poisson equation to the linear systems through the finite difference method, we adopt the Harrow-Hassidim-Lloyd (HHL) algorithm as the basic framework. Particularly, in this work we present an advanced circuit that ensures the accuracy of the solution by implementing non-truncated eigenvalues through eigenvalue amplification as well as by increasing the accuracy of the controlled rotation angular coefficients, which are the critical factors in the HHL algorithm. We show that our algorithm not only increases the accuracy of the solutions, but also composes more practical and scalable circuits by dynamically controlling problem size in the NISQ devices. We present both simulated and experimental results, and discuss the sources of errors. Finally, we conclude that overall results on the quantum hardware are dominated by the error in the CNOT gates.

Robson, Walter↗

Encoding trade-offs and design toolkits in quantum algorithms for discrete optimization: coloring, routing, scheduling, and other problems

Challenging combinatorial optimization problems are ubiquitous in science and engineering. Several quantum methods for optimization have recently been developed, in different settings including both exact and approximate solvers. Addressing this field of research, this manuscript has three distinct purposes. First, we present an intuitive method for synthesizing and analyzing discrete (i.e., integer-based) optimization problems, wherein the problem and corresponding algorithmic primitives are expressed using a discrete quantum intermediate representation (DQIR) that is encoding-independent. This compact representation often allows for more efficient problem compilation, automated analyses of different encoding choices, easier interpretability, more complex runtime procedures, and richer programmability, as compared to previous approaches, which we demonstrate with a number of examples. Second, we perform numerical studies comparing several qubit encodings; the results exhibit a number of preliminary trends that help guide the choice of encoding for a particular set of hardware and a particular problem and algorithm. Our study includes problems related to graph coloring, the traveling salesperson problem, factory/machine scheduling, financial portfolio rebalancing, and integer linear programming. Third, we design low-depth graph-derived partial mixers (GDPMs) up to 16-level quantum variables, demonstrating that compact (binary) encodings are more amenable to QAOA than previously understood. We expect this toolkit of programming abstractions and low-level building blocks to aid in designing quantum algorithms for discrete combinatorial problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Strategic Lens on Quantum Sensing for Space Applications

As classical technologies approach their theoretical power limits, quantum technologies, including computing, communications, and sensing, are often credited as the next science and engineering revolution. Quantum sensors are the basis of quantum computing and communications technologies, but also have unique uses for security, medical, and space-related applications. Regarding NASA’s agency goals, quantum sensing can improve climate change monitoring, enable navigations systems for deep space, and enhance fundamental astrophysics research. This report outlines the findings from an independent intern project on the ways NASA can strategically invest in quantum sensing technologies. This report also outlines policy barriers to developing the technology, largely related to communication difficulties, unfamiliarity with quantum, and lengthy approval processes. The information on tools and challenges relevant to quantum technology was gathered from literature reviews, online research, and discussions with NASA individuals. This report concludes with strategic recommendations to answer the question: what policies should NASA implement to effectively research and develop quantum sensing technologies?

Holland Frieling↗

Quantum-Confined Lifshitz Transition on Weyl Semimetal T d -MoTe 2

Adsorption of alkali atoms onto material surfaces is widely utilized for controlling electronic properties and is particularly effective for two-dimensional materials. While tuning the chemical potential and band gap and creating quantum-confined states are well established for alkali adsorption on semiconductors, the effects on semimetallic systems remain largely elusive. Here, utilizing angle-resolved photoemission spectroscopy measurements and density functional theory calculations, we disclose the creation of two-dimensional electron gas and the quantum-confined Lifshitz transition at the surface of a Weyl semimetal T d -MoTe 2 by potassium adsorption. Electrons from potassium adatoms are shown to be transferred mainly to the lowest unoccupied band within the gapped part of the Brillouin zone, which, in turn, induces strong surface band bending and quantum confinement in the topmost layer. The quantum-confined topmost layer evolves from a semimetal to a strong metal with a Lifshitz transition departing substantially from the bulk band. The present finding and its underlying mechanism can be exploited for the creation of electronic heterojunctions in van der Waals semimetals.

36 MATERIALS SCIENCE↗

Manipulation of the Magnetoresistance by Strain in Topological TaSe 3

1D TaSe 3 exhibits many unusual physical properties due to its distorted type-II chains. Ribbon-shaped single crystals can be easily bended along the $b-axis$, forming rings. This study investigates the magnetoresistance (MR) of TaSe 3 up to 60 T in both unbended (ribbon shape) and ring-shaped (bended ribbon) samples. Notable changes are found in the magnetotransport properties between the two different shaped samples. One is that the MR in ring-shaped samples is three orders lower than that in unbended samples under the same sample environment. In addition, linear MR is observed above ≈20 T in ring-shaped samples when the magnetic field is parallel or perpendicular to the rings. Quantum oscillations are also observed as a function of the magnetic field when the magnetic field is applied parallel to rings, possibly due to the Altshuler–Aronov–Spivak effect or the inversion of the lowest Landau level beyond the quantum limit. All these results are related to strain-induced electronic structure change in TaSe 3 , an effective way to tune physical properties in low-dimensional materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum Dot–Organic Molecule Conjugates as Hosts for Photogenerated Spin Qubit Pairs

The inherent spin polarization present in photogenerated spin-correlated radical pairs makes them promising candidates for quantum computing and quantum sensing applications. The spin states of these systems can be probed and manipulated with microwave pulses using electron paramagnetic resonance spectrometers. However, to date, there are no reports on magnetic resonance-based spin measurements of photogenerated spin-correlated radical pairs hosted on quantum dots. In the current work, we prepare dye molecule-inorganic quantum dot conjugates and show that they can produce photogenerated spin-polarized states. The dye molecule, D131, is chosen for its ability to undergo efficient charge separation, and the nanoparticle materials, ZnO quantum dots, are chosen for their promising spin properties. Transient and steady state optical spectroscopy performed on ZnO quantum dot-D131 conjugates shows that reversible photogenerated charge separation is occurring. Transient and pulsed electron paramagnetic resonance experiments are then performed on the photogenerated radical pair, which demonstrate that (1) the radical pair is polarized at moderate temperatures and well modeled by existing theories and (2) the spin states can be accessed and manipulated with microwave pulses. In conclusion, this work opens the door to a new class of promising qubit materials that can be photogenerated in polarized states and hosted by highly tailorable inorganic nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards large-scale quantum optimization solvers with few qubits

Quantum computers hold the promise of more efficient combinatorial optimization solvers, which could be game-changing for a broad range of applications. However, a bottleneck for materializing such advantages is that, in order to challenge classical algorithms in practice, mainstream approaches require a number of qubits prohibitively large for near-term hardware. Here we introduce a variational solver for MaxCut problems over $m={{\mathcal{O}}}({n}^{k})$ binary variables using only n qubits, with tunable k > 1. The number of parameters and circuit depth display mild linear and sublinear scalings in m , respectively. Moreover, we analytically prove that the specific qubit-efficient encoding brings in a super-polynomial mitigation of barren plateaus as a built-in feature. Altogether, this leads to high quantum-solver performances. For instance, for m = 7000, numerical simulations produce solutions competitive in quality with state-of-the-art classical solvers. In turn, for m = 2000, experiments with n = 17 trapped-ion qubits feature MaxCut approximation ratios estimated to be beyond the hardness threshold 0.941. Our findings offer an interesting heuristics for quantum-inspired solvers as well as a promising route towards solving commercially-relevant problems on near-term quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Anisotropic phase stiffness in infinite-layer nickelates superconductors

In unconventional superconductors such as cuprates and iron pnictides and chalcogenides, phase stiffness—a measure of the energy cost associated with superconducting phase variations—governs the formation of superconductivity. Here we demonstrate a vector current technique enabling in-situ angle-resolved transport measurements to reveal anisotropic phase stiffness in infinite-layer nickelate superconductors. Pronounced anisotropy of in-plane resistance manifests itself in both normal and superconducting transition states, indicating crystal symmetry breaking. Remarkably, the electric conductivity of Nd 0.8 Sr 0.2 NiO 2 peaks at 125° between the direction of the current and crystal principal axis, but this angle evolves to 160° near zero-resistance temperature. Further measurements reveal that the phase stiffness maximizes along 160°, a direction distinct from the symmetry axis imposed by both electronic nematicity and the crystal lattice. Identical measurements conducted on a prototypical cuprate superconductor yield consistent results. By identifying the contrasting anisotropy between electron fluid and superfluid in both nickelates and cuprates, our findings provide clues for a unified framework for understanding unconventional superconductors.

Xu, Minyi [University of Electronic Science and Te↗

Single nuclear spin detection and control in a van der Waals material

Optically active spin defects in solids are leading candidates for quantum sensing and quantum networking. Recently, single spin defects were discovered in hexagonal boron nitride (hBN), a layered van der Waals (vdW) material. Owing to its two-dimensional structure, hBN allows spin defects to be positioned closer to target samples than in three-dimensional crystals, making it ideal for atomic-scale quantum sensing, including nuclear magnetic resonance (NMR) of single molecules. However, the chemical structures of these defects remain unknown and detecting a single nuclear spin with a hBN spin defect has been elusive. Here we report the creation of single spin defects in hBN using 13 C ion implantation and the identification of three distinct defect types based on hyperfine interactions. We observed both S = 1/2 and S = 1 spin states within a single hBN spin defect. We demonstrated atomic-scale NMR and coherent control of individual nuclear spins in a vdW material, with a π-gate fidelity up to 99.75% at room temperature. By comparing experimental results with density functional theory (DFT) calculations, we propose chemical structures for these spin defects. Our work advances the understanding of single spin defects in hBN and provides a pathway to enhance quantum sensing using hBN spin defects with nuclear spins as quantum memories.

Quantum metrology↗

Generation of thermofield double states and critical ground states with a quantum computer

Significance Our experiment prepares two types of nontrivial quantum states on a trapped ion quantum computer: the thermofield double state of the transverse-field Ising model at arbitrary temperature and the quantum critical state of the zero-temperature model. We use techniques motivated by the quantum approximate optimization algorithm, and we implement a hybrid quantum–classical optimization loop to prepare the quantum critical state. Our results pave the way for exploring strongly correlated models at finite temperature and teleportation protocols inspired by black hole physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

From crystal color symmetry to quantum spacetime

More than one hundred years after the inception of relativistic physics, the concept of time remains incompletely understood. Relativity provides means to perform calculations of geometrical properties of spacetime, such as distances or curvature, and to interpret them in terms of physical observations, for instance as time dilation or gravitational effects. However, an intuitive understanding of spacetime is complicated, not so much because it is four-dimensional (which, after all, can be evaded by visualizing twodimensional cross sections) but mainly because its geometry does not obey Euclid’s axioms even in the absence of curvature. Through a well defined and clever transformation (RBS: renormalized blended spacetime), Venkatraman Gopalan (2021) has demonstrated how the hyperbolic geometry in Minkowski spacetime can be mapped to a circular Euclidean geometry. In particular, Lorentzian boosts become Euclidean rotations which enables new frontiers of exploration in color symmetry and magnetic crystals. His idea of general relativistic spacetime crystals and how to obtain them is both powerful and broad, although the notion of relativistic crystals and lattices in two dimensions has existed for a while (Janner & Ascher, 1969a,b). Finally, the breadth of this new work is underlined by the present opinion piece, written by two co-authors with distinct yet connected areas of expertise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Numerical evidence against advantage with quantum fidelity kernels on classical data

Quantum machine learning techniques are commonly considered one of the most promising candidates for demonstrating practical quantum advantage. In particular, quantum kernel methods have been demonstrated to be able to learn certain classically intractable functions efficiently if the kernel is well aligned with the target function. In the more general case, quantum kernels are known to suffer from exponential “flattening” of the spectrum as the number of qubits grows, preventing generalization and necessitating the control of the inductive bias by hyperparameters. We show that the general-purpose hyperparameter-tuning techniques proposed to improve the generalization of quantum kernels lead to the kernel becoming well approximated by a classical kernel, removing the possibility of quantum advantage. We provide extensive numerical evidence for this phenomenon utilizing multiple previously studied quantum feature maps and both synthetic and real data. Our results show that unless novel techniques are developed to control the inductive bias of quantum kernels, they are unlikely to provide a quantum advantage on classical data that lacks special structure.

Quantum Information, Science & Technology↗