In recent years, there have been significant advancements in various aspects of quantum computing. However, despite this substantial progress, the availability of fault-tolerant quantum computers is still out of reach and may remain so for decades. Therefore, a key challenge is to leverage current NISQ devices to achieve a quantum advantage effectively. In this context, the Quantum Approximate Optimization Algorithm (QAOA) was proposed to potentially demonstrate computational advantages in combinatorial optimization problems using NISQ computers. Meanwhile, quantum error mitigation (QEM) techniques have been developed to address errors, with their effectiveness validated in practical problems involving more than 100 qubits. Therefore, in this paper, we optimize QAOA circuits and apply various error mitigation methods, such as dynamic decoupling and Pauli-twirling, to scale problem sizes on IBM quantum processors. Additionally, we discuss optimal implementation strategies for scalable QAOA. We test our implementations on Max-Cut problems and compare our results with previous works.
In recent years, significant progress has been made in building quantum computers by several companies. Despite the progress, these noisy intermediate-scale quantum (NISQ) computers still suffer from several noises and errors such as measurement errors, multi-qubit gate errors, and worse, short decoherence times. Though quantum computer vendors are releasing better quantum computers in terms of Quantum Volume, the quantum device still remains far from quantum supremacy in practical problems. The Quantum Approximate Optimization Algorithm (QAOA) was suggested to potentially demonstrate a computational advantage in combinatorial optimization problems on NISQ computers. In this paper, we optimize the QAOA circuits and to scale the problem size on IBM quantum processors. In addition, we study the effect of the length of the QAOA ansatz on IBM quantum processors and discuss optimal implementation methods for scalable QAOA. We test our implementations on the MaxCut problems.
The quantum annealing devices, which encode the solution to a computational problem in the ground state of a quantum Hamiltonian, are implemented in D-Wave systems with more than 2,000 qubits. However, quantum annealing can solve only a classical combinatorial optimization problem such as an Ising model, or equivalently, a quadratic unconstrained binary optimization (QUBO) problem. In this paper, we formulate the QUBO model to solve elliptic problems with Dirichlet and Neumann boundary conditions using the finite element method. In this formulation, we develop the objective function of quadratic binary variables represented by qubits and the system finds the binary string combination minimizing the objective function globally. Based on the QUBO formulation, we introduce an iterative algorithm to solve the elliptic problems. We discuss the validation of the modeling on the D-Wave quantum annealing system.
Growing interest in quantum machine learning has resulted into very innovative algorithms and vigorous studies that demonstrate their power. These studies, although very useful, are often designed for fault-tolerant quantum computers that are far from reality of today's noise-prone quantum computers. While companies such as IBM have ushered in a new era of quantum computing by allowing public access to their quantum computers, quantum noise as well as decoherence are daunting obstacles that not only degrade the performance of quantum algorithms, but also make them infeasible for running on current-era quantum processors. We address the feasibility of a quantum machine learning algorithm on IBM quantum processors to shed light on their efficacy and weaknesses to design noise-aware algorithms that work around these limitations. We compare and discuss the results by implementing a quantum convolutional filter on a real quantum processor as well as a simulator.
Radiation sources from Langmuir waves has been a topic of interest for their relevance to experimental approaches in plasma laboratories as well as for estimating physical models to explain cosmic radio bursts. Since the mechanism for converting energy from electrostatic Langmuir waves to electromagnetic waves is complex, diverse scenarios of such energy conversion have been studied, e.g. mode conversion, antenna radiation, nonlinear scattering, etc. Previously, we introduced a novel perspective of plasma dipole oscillation (PDO) which generates strong radiation bursts at the plasma frequency and high harmonics. In this paper, we report our discovery of radiation that result from electron-laser beam driven Langmuir waves and their interactions. In 2-D PIC simulations, we have observed that obliquely colliding Langmuir waves or even a single Langmuir wave generate localized radiation sources at the plasma frequency and high harmonics. These mechanisms differ from conventional two-plasmon mergers, where only the second harmonic of the plasma frequency is dominant: a strong radiation is observed even at the fundamental harmonic. In addition, from 3-D PIC simulations of electron laser beam driven plasma oscillators in magnetized plasma, the radiation from a local plasma oscillator, i.e. PDO, is found to be robust with diverse spectral peaks at the X-mode and the upper-hybrid mode. Nonlinear theory demonstrates that the relative strength of the harmonics of the plasma frequency depends on the shape of the PDO. The studies imply that the PDO has a more complicated internal structure than the simple model of a solid charge. We discuss the potential of the PDO generated from electron-beam driven plasmas or laser-driven plasmas as a radiation source and its relevance to cosmic radio bursts.
Laser-plasma interactions have many theoretical and technological applications. One is the use of coherently accelerated electrons to provide novel sources of THz radiation. Our research focuses on simulating the cross/self-interactions between two high intensity, ultra-short, counter propagating and detuned laser pulses and an initial neutral target for controlled ionization. Unlike our previous studies of laser-matter interaction over preformed plasma, we explore the injection and collision of laser pulses to induce background plasma driven by the self-guided laser wakefield mechanism, which is then used to perturb the plasma resulting in induced dipole oscillations leading to transverse radiation. Inducing a cylindrical spatial plasma column within the laser beam radius regime provides a stable, spatially localized plasma channel. The emitted radiation from the plasma dipole oscillation (PDO) will not be affected by surrounding plasma absorption, resulting in effective radiation distribution. Results include 3D EM-PIC simulations and a comparison of the self- ionizing plasma against the preformed plasma to assess the efficiency of the mechanisms.
Methane and Nitrous Oxide are long-lived greenhouse gases in the atmosphere with significant global warming effects. We report on application of chirped-pulsed quantum cascade lasers (QCLs) to simultaneous measurements of these trace gases in both open-path fence-line and backscatter systems. The intra-pulse thermal frequency chip in a QCL can be time resolved and calibrated to allow for high resolution differential optical absorption spectroscopy over the spectral window of the chip, which for a DFB-QCL can be reach ~2cm-1 for a 500 nsec pulse. The spectral line-shape of the output from these lasers are highly stable from pulse to pulse over long period of time (> 1 day), and the system does not require frequent calibrations.
Fugitive gas emissions from agricultural or industrial plants and gas pipelines are an important environmental concern as they can contribute to the global increase of greenhouse gas concentration. Moreover, they are also a security and safety concern because of possible risk of fire/explosion or toxicity. This study presents gas concentration measurements using a quantum cascade laser open path system (QCLOPS). The system retrieves the path-averaged concentration of N2O by collecting the backscattered light from a scattering target. The gas concentration measurements have a high temporal resolution (68 ms) and are achieved at sufficient range (up to 40 m, ~ 130 feet) with a detection limit of 0.4 ppm for N2O. Given these characteristics, this system is promising for mobile/multidirectional remote detection and evaluation of gas leaks.
Quantum Cascade Lasers (QCL’s) have been successfully used to monitor atmospheric pollutants in the mid-infrared
(mid-IR) region. However, their use for multiple gases in ambient conditions is less familiar. This paper explores the
performance of a novel field deployable open path system based on a chirped single distributed-feedback QCL. In
particular, we report both laboratory and open path measurements for simultaneous detection of two greenhouse gases
(GHG) methane (CH4) and nitrous oxide. (N2O). We focused on CH4 and N2O because they are long-lived greenhouse
gases in the atmosphere with significant global warming effects.
Gas spectra were recorded by tuning the QC laser wavelength using a thermal down chirp technique over 1297–1300
cm-1 optimal spectral window with 0.008 cm-1 spectral resolution. Based on careful optimization of the spectral window
for absorption features of CH4 and N2O, a dual-species, cost-effective, robust and rapid response open-path laser based
monitor has been developed for ambient trace gas monitoring.
Theoretical signal to noise ratio (SNR) analysis of the system based on an ideal system is briefly discussed in the paper
but our main focus is on actual system performance, long term stability and systemic errors. Finally, preliminary results
of the open path system are reported.
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