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We describe solutions of the matrix equation exp(z(A − I{sub n})) = A, where z ∈ ℂ. Applications in quantum computing are given. Both normal and non-normal matrices are studied. For normal matrices, the Lambert W-function plays a central role.
The problem of speeding up quantum computations through controlling the states of qubits by short large-amplitude unipolar pulses is discussed. A new method is proposed to describe the dynamics of qubits that is based on the Magnus representation for the evolution operator (propagator) of qubits, which allows one to find a solution to the quantum control problem outside the framework of perturbation theory. The evolution of the states of a multiqubit system is represented as a motion on a special unitary group SU(N), similar to the rotation of the Bloch vector on the group SU(2) in the case of a single qubit. As an example, unitary transformations of single-qubit states under different excitation modes are considered. A general formula is found that establishes a relation between the shape of a pulse and the result of its action, similar to the well-known “area theorem” for Rabi pulses. The effect of unipolar pulses on a two-qubit system is analyzed in detail. Two situations are considered: first, a symmetric configuration, when the parameters of qubits do not differ and are acted upon by the same magnetic field from a fluxon, and second, when the configuration of levels arises in which, for one of the qubits, a transition to the nearest level becomes possible under perturbation. The general case of two interacting qubits—a four-level system—is considered analytically. A direct numerical simulation of the dynamics of a multiqubit system is performed to estimate the accuracy of approximation, and fidelity is used as a criterion of accuracy of operations. It is shown that the expressions obtained for the propagator allow one to formulate conditions for the pulse parameters that are necessary to perform logical operations.
The U.S. National Quantum Initiative places quantum computer scaling in the same category as Moore's law. While the technical basis of semiconductor scale up is well known, the equivalent principle for quantum computers is still being developed here. Let's explore these new ideas.
The proper identification of the molecular nature of the aged rhenium compound obtained by means of electrodeposition from an alkaline aqueous electrolyte was determined. Chemical, structural and vibrational experimental characterization of the aged Re compound showed agreement with quantum-computations, thereby allowing the unambiguous identification of the Re compound as H(ReO{sub 4})H{sub 2}O. - Graphical abstract: Rhenium oxides were electrodeposited on a copper surface and after environmental aging was formed the H(ReO{sub 4})H{sub 2}O compound. The characterization of the synthesized material was made through the comparison of experimental evidence with quantum mechanical computations carried out by means of density functional theory (DFT). - Highlights: • Aged rhenium compound obtained by means of electrodeposition was studied. • The study was made by combining experimental and DFT-computational information. • The aged electrodeposited material is consistent with the H(ReO{sub 4})H{sub 2}O compound.
While quantum annealers have emerged as versatile and controllable platforms for experimenting on correlated spin systems, the important phenomenology of magnetic memory and hysteresis remain unexplored on hardware designed to escape metastable states via quantum tunneling. Here, we present the first general protocol to experiment on magnetic hysteresis on programmable quantum annealers and implement it on three D-Wave superconducting qubit quantum annealers, using up to thousands of spins, for both ferromagnetic and disordered Ising models, and across different graph topologies. We observe hysteresis loops whose area depends nonmonotonically on quantum fluctuations, exhibiting both expected and unexpected features, such as disorder-induced steps and nonmonotonicities. Our work establishes quantum annealers as a platform for probing nonequilibrium emergent magnetic phenomena, thereby broadening the role of analog quantum computers into foundational questions in condensed matter physics.
For potential applications in spintronics and quantum computing, it is desirable to place a quantum spin Hall insulator [i.e., a 2D topological insulator (TI)] on a substrate while maintaining a large energy gap. Here, we demonstrate a unique approach to create the large-gap 2D TI state on a semiconductor surface, based on first-principles calculations and effective Hamiltonian analysis. We show that when heavy elements with strong spin orbit coupling (SOC) such as Bi and Pb atoms are deposited on a patterned H-Si(111) surface into a hexagonal lattice, they exhibit a 2D TI state with a large energy gap of ≥0.5 eV. The TI state arises from an intriguing substrate orbital filtering effect that selects a suitable orbital composition around the Fermi level, so that the system can be matched onto a four-band effective model Hamiltonian. Furthermore, it is found that within this model, the SOC gap does not increase monotonically with the increasing strength of SOC. These interesting results may shed new light in future design and fabrication of large-gap topological quantum states.
Variational hybrid quantum-classical algorithms (VHQCAs) are near-term algorithms that leverage classical optimization to minimize a cost function, which is efficiently evaluated on a quantum computer. Recently VHQCAs have been proposed for quantum compiling, where a target unitary U is compiled into a short-depth gate sequence V. In this work, we report on a surprising form of noise resilience for these algorithms. Namely, we find one often learns the correct gate sequence V (i.e. the correct variational parameters) despite various sources of incoherent noise acting during the cost-evaluation circuit. Our main results are rigorous theorems stating that the optimal variational parameters are unaffected by a broad class of noise models, such as measurement noise, gate noise, and Pauli channel noise. Furthermore, our numerical implementations on IBM's noisy simulator demonstrate resilience when compiling the quantum Fourier transform, Toffoli gate, and W-state preparation. Hence, variational quantum compiling, due to its robustness, could be practically useful for noisy intermediate-scale quantum devices. Finally, we speculate that this noise resilience may be a general phenomenon that applies to other VHQCAs such as the variational quantum eigensolver.
Progress toward the solution of the strongly correlated electron problem has been stymied by the exponential complexity of the wave function. Previous work established an exact two-body exponential product expansion for the ground-state wave function. By developing a reduced density-matrix analog of Dalgarno-Lewis perturbation theory, we prove here that (i) the two-body exponential product expansion is rapidly and globally convergent with each operator representing an order of a renormalized perturbation theory, (ii) the energy of the expansion converges quadratically near the solution, and (iii) the expansion is exact for both ground and excited states. The two-body expansion offers a reduced parametrization of the many-particle wave function as well as the two-particle reduced density matrix with potential applications on both conventional and quantum computers for the study of strongly correlated quantum systems. In this work, we demonstrate the result with the exact solution of the contracted Schrödinger equation for the molecular chains H 4 and H 5 .
Qubit state detection is an important part of a quantum computation. As number of qubits in a quantum register increases, it is necessary to maintain high fidelity detection to accurately measure the multi-qubit state. Here we present experimental demonstration of high-fidelity detection of a multi-qubit trapped ion register with average single qubit detection error of 4.2(1.5) ppm and a 4-qubit state detection error of 17(2) ppm, limited by the decay lifetime of the qubit, using a novel single-photon-sensitive camera with fast data collection, excellent temporal and spatial resolution, and low instrumental crosstalk.
Advanced simulations and calculations on quantum computers require high-fidelity implementations of quantum operations. The universal gateset approach builds complex unitaries from a small set of primitive gates, often resulting in a long gate sequence, which is typically a leading factor in the total accumulated error. Compiling a complex unitary for processors with higher-dimensional logical elements, such as qutrits, exacerbates the accumulated error per unitary, since an even longer gate sequence is required. Optimal control methods promise time- and resource-efficient compact gate sequences and, therefore, higher fidelity. These methods generate pulses that can directly implement any complex unitary on a quantum device. In this work, we demonstrate that any arbitrary qubit and qutrit gate can be realized with high fidelity, which can significantly reduce the length of a gate sequence. We generate and test pulses for a large set of randomly selected arbitrary unitaries on several quantum processing units (QPUs): the Lawrence Livermore National Laboratory Quantum Device and Integration Testbed’s (QuDIT’s) standard QPU and three of Rigetti’s QPUs: Ankaa-2, Ankaa-9Q-1, and Aspen-M-3. On the QuDIT platform’s standard QPU, the average fidelity of random qutrit gates is 97.9 ± 0.5% measured with conventional QPT and 98.8 ± 0.6% from QPT with gate folding. Rigetti’s Ankaa-2 achieves random qubit gates with an average fidelity of 98.4 ± 0.5% (conventional QPT) and 99.7 ± 0.1% (QPT with gate folding). On Ankaa-9Q-1 and Aspen-M-3, the average fidelities with conventional qubit QPT measurements were higher than 99% (see Appendix). Here we show that optimal control gates are robust to drift for at least 3 h and that the same calibration parameters can be used for all implemented gates. Our work promises that the calibration overheads for optimal control gates can be made small enough to enable efficient quantum circuits based on this technique.
Quantum computers can efficiently simulate the dynamics of quantum systems. Here, we study the cost of digitally simulating the dynamics of several physically relevant systems using the first-order product-formula algorithm. We show that the errors from different Trotterization steps in the algorithm can interfere destructively, yielding a much smaller error than previously estimated. In particular, we prove that the total error in simulating a nearest-neighbor interacting system of n sites for time t using the first-order product formula with r time slices is O ( n t / r + n t 3 / r 2 ) when n t 2 / r is less than a small constant. Given an error tolerance ϵ , the error bound yields an estimate of max { O ( n 2 t / ϵ ) , O ( n 2 t 3 / 2 / ϵ 1 / 2 ) } for the total gate count of the simulation. The estimate is tighter than previous bounds and matches the empirical performance observed in Childs et al. [ Proc. Natl. Acad. Sci. U.S.A. 115 , 9456 (2018) ]. We also provide numerical evidence for potential improvements and conjecture an even tighter estimate for the gate count.
Quantum Gate Synthesis is the process of taking a desired quantum gate operation, in this case specified as a unitary matrix, and decomposing it into a list of operations that can actually be performed on a quantum computer. Qsearch is an implementation of a quantum synthesis algorithm based on combining A* search with numerical optimization. It is designed to minimize CNOT count at the expense of having a long runtime. It produces particularly efficient quantum circuits in terms of CNOT count, up until about 4 qubits. It is generally impractical to run Qsearch on circuits with more than 4 qubits, but it can be used as a subroutine in algorithms designed to work with these larger circuits. Qsearch takes the form of a Python package, taking advantage of Numpy and Scipy, with part of the package written in Rust and taking advantage of OpenBLAS, NLOPT, and Google Ceres for faster runtime.
Advances in laser technology have driven discoveries in atomic, molecular, and optical (AMO) physics and emerging applications, from quantum computers with cold atoms or ions, to quantum networks with solid-state color centers. This progress is motivating the development of a new generation of optical control systems that can manipulate the light field with high fidelity at wavelengths relevant for AMO applications. These systems are characterized by criteria: (C1) operation at a design wavelength of choice in the visible (VIS) or near-infrared (IR) spectrum, (C2) a scalable platform that can support large channel counts, (C3) high-intensity modulation extinction and (C4) repeatability compatible with low gate errors, and (C5) fast switching times. Here, we provide a pathway to address these challenges by introducing an atom control architecture based on VIS-IR photonic integrated circuit (PIC) technology. Based on a complementary metal–oxide–semiconductor fabrication process, this atom-control PIC (APIC) technology can meet system requirements (C1)–(C5). As a proof of concept, we demonstrate a 16-channel silicon-nitride-based APIC with (5.8±0.4)ns response times and >30dB extinction ratio at a wavelength of 780 nm.
The last year of this award we have continued our research on using quantum machine learning to identify phase transitions. By combining quantum machine learning with quantum computing, we extended a hybrid classical-quantum algorithm to capture the metal-insulator quantum phase transition of the Hubbard model. We have also continued our studies of non-equilibrium dynamics of interacting disordered systems. In particular, we studied the non-equilibrium transient dynamics of a system described by the Anderson-Hubbard model following an interaction and disorder quench, and the effect of disorder on the out-of-time-order correlator on the Hubbard model.
QuanSimBench is a software program that performs a gate-by-gate simulation of a quantum computer with a full state vector formulation. It simulates a simplified version of Shor's algorithm with increasing number of qubits until resources are exhausted. The score (states/s) is how fast the Approximate Quantum Fourier Transform can be computed (the modular exponentiation is not timed). The goal is to quantify the ability of a computer to simulate ideal quantum circuits.
Fault-tolerant syndrome extraction is a key ingredient in implementing fault-tolerant quantum computation. While conventional methods use a number of extra qubits that are linear in the weight of the syndrome, several improvements have been introduced using flag gadgets. In this work, we develop a framework to design flag gadgets using classical codes. Using this framework, we show how to perform fault-tolerant syndrome extraction for any stabilizer code with arbitrary distance using exponentially fewer qubits than conventional methods when qubit measurement and reset are relatively slow compared to a round of error correction. In particular, our method requires only ( 2 t + 1 ) t ⌈ log 2 ( w ) ⌉ flag qubits to fault-tolerantly measure a weight- w stabilizer. We further take advantage of the saving provided by our construction to fault-tolerantly measure multiple stabilizers using a single gadget and show that it maintains the same exponential advantage when it is used to fault-tolerantly extract the syndromes of quantum low-density parity-check codes. Using the developed framework, we perform computer-assisted search to find several small examples where our constructions reduce the number of qubits required. These small examples may be relevant to near-term experiments on small-scale quantum computers. Published by the American Physical Society 2024
Orbital angular momentum associated with the helical phase-front of optical beams provides an unbounded “space” for both classical and quantum communications. Among the different approaches to generate and manipulate orbital angular momentum states of light, coupling between spin and orbital angular momentum allows a faster manipulation of orbital angular momentum states because it depends on manipulating the polarisation state of light, which is simpler and generally faster than manipulating conventional orbital angular momentum generators. In this work, we design and fabricate an ultra-thin spin-to-orbital angular momentum converter, based on plasmonic nano-antennas and operating in the visible wavelength range that is capable of converting spin to an arbitrary value of orbital angular momentum ℓ. The nano-antennas are arranged in an array with a well-defined geometry in the transverse plane of the beam, possessing a specific integer or half-integer topological charge q. When a circularly polarised light beam traverses this metasurface, the output beam polarisation switches handedness and the orbital angular momentum changes in value by ℓ=±2qℏ per photon. We experimentally demonstrate ℓ values ranging from ±1 to ±25 with conversion efficiencies of 8.6% ± 0.4%. Our ultra-thin devices are integratable and thus suitable for applications in quantum communications, quantum computations, and nano-scale sensing.
Abstract Quantum computing is a rapidly growing field with the potential to change how we solve previously intractable problems. Emerging hardware is approaching a complexity that requires increasingly sophisticated programming and control. Scaffold is an older quantum programming language that was originally designed for resource estimation for far-future, large quantum machines, and ScaffCC is the corresponding LLVM-based compiler. For the first time, we provide a full and complete overview of the language itself, the compiler as well as its pass structure. While previous works Abhari et al (2015 Parallel Comput. 45 2–17), Abhari et al (2012 Scaffold: quantum programming language https://cs.princeton.edu/research/techreps/TR-934-12 ), have piecemeal descriptions of different portions of this toolchain, we provide a more full and complete description in this paper. We also introduce updates to ScaffCC including conditional measurement and multidimensional qubit arrays designed to keep in step with modern quantum assembly languages, as well as an alternate toolchain targeted at maintaining correctness and low resource count for noisy-intermediate scale quantum (NISQ) machines, and compatibility with current versions of LLVM and Clang. Our goal is to provide the research community with a functional LLVM framework for quantum program analysis, optimization, and generation of executable code.