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Bhaskar Roy Bardhan

Publications and source records attributed to Bhaskar Roy Bardhan.

12 recordsLinked to original sources

Hybrid quantum optimization in the context of minimizing traffic congestion

Traffic optimization on roads is a highly complex problem, with one important aspect being minimization of traffic congestion. By mapping to an Ising formulation of the traffic congestion problem, we benchmark solutions obtained from the Quantum Approximate optimization Algorithm (QAOA), a hybrid quantum-classical algorithm. In principle, as the number of QAOA layers approaches infinity, the solutions should reach optimality. On the other hand, short-depth QAOA circuits are known to have limited performance. We show that using tailored initialization techniques encourages the convergence to the desired solution state at lower circuit depths with two and three QAOA layers, thus highlighting the importance of adapting quantum algorithms in the noisy intermediate scale (NISQ) quantum computing era. Moreover, for NISQ devices with limited qubit connectivity and circuit depth, we introduce a heuristic noise-resilient variant of QAOA predicated on the elimination of long-range 2-qubit interactions in the QAOA layers whilst the cost function is unaltered. Our results show that this QAOA variant is surprisingly effective, outperforming QAOA on a physical IBM Quantum computer device.

quant-ph

Quantum-Inspired Optimization over Permutation Groups

Quantum-inspired optimization (QIO) algorithms are computational techniques that emulate certain quantum mechanical effects on a classical hardware to tackle a class of optimization tasks. QIO methods have so far been employed to solve various binary optimization problems and a significant (polynomial) computational speedup over traditional techniques has also been reported. In this work, we develop an algorithmic framework, called Perm-QIO, to tailor QIO tools to directly solve an arbitrary optimization problem, where the domain of the underlying cost function is defined over a permutation group. Such problems are not naturally recastable to a binary optimization and, therefore, are not necessarily within the scope of direct implementation of traditional QIO tools. We demonstrate the efficacy of Perm-QIO in leveraging the structure of cost-landscape to find high-quality solutions for a class of vehicle routing problems that belong to the category of non-trivial combinatorial optimization over the space of permutations.

quant-ph

Towards quantum simulation of spin systems using continuous variable quantum devices

We study Bosonic representation of spin Ising model with the application of simulating two level systems using continuous variable quantum processors. We decompose the time evolution of spin systems into a sequence of continuous variable logical gates and analyze their structure. We provide an estimation of quantum circuit scaling with the size of the spin lattice system. Furthermore, we discuss the possibility of using a Gaussian Boson sampling device to estimate the ground state energy of Ising Hamiltonian. The result has potential application in developing hybrid classical-quantum algorithms such as continuous variable version of variational quantum eigensolver.

quant-ph

Quantum-inspired algorithms in practice

We study the practical performance of quantum-inspired algorithms for recommendation systems and linear systems of equations. These algorithms were shown to have an exponential asymptotic speedup compared to previously known classical methods for problems involving low-rank matrices, but with complexity bounds that exhibit a hefty polynomial overhead compared to quantum algorithms. This raised the question of whether these methods were actually useful in practice. We conduct a theoretical analysis aimed at identifying their computational bottlenecks, then implement and benchmark the algorithms on a variety of problems, including applications to portfolio optimization and movie recommendations. On the one hand, our analysis reveals that the performance of these algorithms is better than the theoretical complexity bounds would suggest. On the other hand, their performance as seen in our implementation degrades noticeably as the rank and condition number of the input matrix are increased. Overall, our results indicate that quantum-inspired algorithms can perform well in practice provided that stringent conditions are met: low rank, low condition number, and very large dimension of the input matrix. By contrast, practical datasets are often sparse and high-rank, precisely the type that can be handled by quantum algorithms.

quant-ph

Advances in Photonic Quantum Sensing

Quantum sensing has become a mature and broad field. It is generally related with the idea of using quantum resources to boost the performance of a number of practical tasks, including the radar-like detection of faint objects, the readout of information from optical memories or fragile physical systems, and the optical resolution of extremely close point-like sources. Here we first focus on the basic tools behind quantum sensing, discussing the most recent and general formulations for the problems of quantum parameter estimation and hypothesis testing. With this basic background in our hands, we then review emerging applications of quantum sensing in the photonic regime both from a theoretical and experimental point of view. Besides the state-of-the-art, we also discuss open problems and potential next steps.

quant-ph

Effects of Temperature and Near Ultraviolet Light on Current-Voltage Characteristics of Colemanite

We investigate current-voltage (I-V) characteristics of the ferroelectric material colemanite at room temperature, at a high temperature, and also under the influence of near ultraviolet light. We demonstrate that all three I-V plots exhibit hysteresis effects, and these new results shed new light on the resistance of colemanite. These novel properties are explained on the basis of its microstructure indicating potential applications in devices with negative resistance as well as in photovoltaic devices.

cond-mat.mtrl-sci

Ultimate Capacity of a Linear Time-Invariant Bosonic Channel

We determine the ultimate classical information capacity of a linear time-invariant bosonic channel with additive phase-insensitive Gaussian noise. This channel can model fiber-optic communication at power levels below the threshold for significant nonlinear effects. We provide a general continuous-time result that gives the ultimate capacity for such a channel operating in the quasimonochromatic regime under an average power constraint. This ultimate capacity is compared with corresponding results for heterodyne and homodyne detection over the same channel.

quant-ph

Strong converse for the classical capacity of optical quantum communication channels

We establish the classical capacity of optical quantum channels as a sharp transition between two regimes---one which is an error-free regime for communication rates below the capacity, and the other in which the probability of correctly decoding a classical message converges exponentially fast to zero if the communication rate exceeds the classical capacity. This result is obtained by proving a strong converse theorem for the classical capacity of all phase-insensitive bosonic Gaussian channels, a well-established model of optical quantum communication channels, such as lossy optical fibers, amplifier and free-space communication. The theorem holds under a particular photon-number occupation constraint, which we describe in detail in the paper. Our result bolsters the understanding of the classical capacity of these channels and opens the path to applications, such as proving the security of noisy quantum storage models of cryptography with optical links.

quant-ph

Strong converse rates for classical communication over thermal and additive noise bosonic channels

We prove that several known upper bounds on the classical capacity of thermal and additive noise bosonic channels are actually strong converse rates. Our results strengthen the interpretation of these upper bounds, in the sense that we now know that the probability of correctly decoding a classical message rapidly converges to zero in the limit of many channel uses if the communication rate exceeds these upper bounds. In order for these theorems to hold, we need to impose a maximum photon number constraint on the states input to the channel (the strong converse property need not hold if there is only a mean photon number constraint). Our first theorem demonstrates that Koenig and Smith's upper bound on the classical capacity of the thermal bosonic channel is a strong converse rate, and we prove this result by utilizing the structural decomposition of a thermal channel into a pure-loss channel followed by an amplifier channel. Our second theorem demonstrates that Giovannetti et al.'s upper bound on the classical capacity of a thermal bosonic channel corresponds to a strong converse rate, and we prove this result by relating success probability to rate, the effective dimension of the output space, and the purity of the channel as measured by the Renyi collision entropy. Finally, we use similar techniques to prove that similar previously known upper bounds on the classical capacity of an additive noise bosonic channel correspond to strong converse rates.

quant-ph

Dynamical decoupling with tailored waveplates for long distance communication using polarization qubits

We address the issue of dephasing effects in flying polarization qubits propagating through optical fiber by using the method of dynamical decoupling. The control pulses are implemented with half waveplates suitably placed along the realistic lengths of the single mode optical fiber. The effects of the finite widths of the waveplates on the polarization rotation are modeled using tailored refractive index profiles inside the waveplates. We show that dynamical decoupling is effective in preserving the input qubit state with the fidelity close to one when the polarization qubit is subject to the random birefringent noise in the fiber, as well the rotational imperfections (flip-angle errors) due to the finite width of the waveplates.

quant-ph

Effects of Phase Fluctuations on Phase Sensitivity and Visibility of Path-Entangled Photon Fock States

We study effects of phase fluctuations on phase sensitivity and visibility of a class of robust path-entangled photon Fock states (known as mm' states) as compared to the maximally path-entangled N00N states in presence of realistic phase fluctuations such as turbulence noise. Our results demonstrate that the mm' states, which are more robust than the N00N state against photon loss, perform equally well when subject to such fluctuations. We show that the phase sensitivity with parity detection for both of the above states saturates the quantum Cramer-Rao bound in presence of such noise, suggesting that the parity detection presents an optimal detection strategy.

quant-ph

Dynamical Decoupling in Optical Fibers: Preserving Polarization Qubits from Birefringent Dephasing

One of the major challenges in quantum computation has been to preserve the coherence of a quantum system against dephasing effects of the environment. The information stored in photon polarization, for example, is quickly lost due to such dephasing, and it is crucial to preserve the input states when one tries to transmit quantum information encoded in the photons through a communication channel. We propose a dynamical decoupling sequence to protect photonic qubits from dephasing by integrating wave plates into optical fiber at prescribed locations. We simulate random birefringent noise along realistic lengths of optical fiber and study preservation of polarization qubits through such fibers enhanced with Carr-Purcell-Meiboom-Gill (CPMG) dynamical decoupling. This technique can maintain photonic qubit coherence at high fidelity, making a step towards achieving scalable and useful quantum communication with photonic qubits.

quant-ph