arXiv subjects

Chandan Kumar

Publications and source records attributed to Chandan Kumar.

At least 37 records · Page 2Linked to original sources

arXiv2024

Characterisation of Front-End Electronics of ChaSTE experiment onboard Chandayaan-3 lander

Chandra Surface Thermophysical Experiment (ChaSTE) is one of the payloads flown onboard the Chandrayaan-3 lander. The objective of the experiment is in-situ investigation of thermal behaviour of outermost 100 mm layer of the lunar surface by deploying a thermal probe. The probe consists of 10 temperature sensors (Platinum RTDs) mounted at different locations along the length of the probe to measure lunar soil temperatures as a function of depth. A heater is also mounted on the probe for thermal conductivity measurements. The onboard electronics of ChaSTE has two parts, Front-End Electronics (FEE) and processing electronics (PE). The front-end electronics (FEE) card is responsible for carrying out necessary sensor signal conditioning,which includes exciting the RTD sensors,acquiring analog voltages and then converting the acquired analog signals to digital signals using an Analog to Digital Converter(ADC). The front-end card is further interfaced with the processing electronics card for digital processing and spacecraft interface.The calibration, characterisation and functional test activities of Front-End Electronics of ChaSTE were carried out with the objective of testing and ensuring proper functionality and performance.A two phase calibration process involving electronic offset correction and temperature calibration were carried out. All these activities were successfully completed and the results from them provided us with a really good understanding of the behaviour of the FEE under different thermal and electrical conditions as well as when subjected to the simulated conditions of the actual ChaSTE experiment. The performance of the ChaSTE front-end electronics was very much within the design margins and its behaviour in simulated lunar environment was as desired. The data from these activities is useful in the interpretation of the actual science data of ChaSTE.

physics.ins-det↗

arXiv2024

Continuous variable quantum teleportation using photon subtracted and photon added two mode squeezed coherent state

We consider non-Gaussian states generated by photon subtraction (PS) and photon addition (PA) on two-mode squeezed coherent (TMSC) states, as resource states for continuous variable (CV) quantum teleportation (QT). To this end, we derive the Wigner characteristic function for the family of photon subtracted and photon added TMSC states, which is then utilized to calculate the fidelity of teleporting a single mode coherent state and a squeezed vacuum state. The analysis shows that while symmetric PS enhances the fidelity of QT in an extensive range of squeezing, asymmetric PS enhances the performance marginally and only in the low squeezing regime. The addition operations on the other hand are less useful, symmetric three-PA leads to a marginal improvement while the other addition operations are useless. We have considered the actual experimental setup for PS and PA operations and computed their success probabilities which should be kept in mind while advocating the use of these operations. We could compute the fidelity of QT for a broad range of states because we analytically derived the Wigner characteristic function for these family of states which we think will be useful for various other applications of these families of states.

quant-ph↗

arXiv2024

Shear-Layer Perturbation Responses from Time-Resolved Schlieren Data

A novel combination of physics-based and data-driven post-processing techniques is proposed to extract acoustic-related shear-layer perturbation responses directly from spatio-temporally resolved schlieren video. The physics-based component is derived from a momentum potential theory extension that extracts irrotational (acoustic and thermal) information from density gradients embedded in schlieren pixel intensities. For the unheated shear layer, the method spotlights acoustic structures and tones otherwise hidden. The filtered data is then subjected to a data-driven Dynamic Mode Decomposition Reduced Order Model (DMD-ROM), which provides the response to forced perturbations. This method applies a learned linear model to isolate and quantify growth rates of acoustic phenomena suited for efficient parametric studies. A shear-layer comprised of two streams at Mach 2.461 and 0.175, corresponding to a convective Mach number 0.88 and containing shocks, is adopted for illustration. The overall perturbation response is first obtained using an impulse forcing in the wall normal direction of the splitter plate, extending in both subsonic and supersonic streams. Subsequently, impulse and harmonic forcings are independently applied in a local pixel-by-pixel manner for a precise receptivity study. The acoustic response shows a convective wavepacket and an acoustic burst from the splitter plate. The interaction with the primary shock and associated wave dispersion emits a second, slower, acoustic wave. Harmonic forcing indicates higher frequency-dependent sensitivity in the supersonic stream, with the most sensitive location near the outer boundary layer region. Excitation here yields an order of magnitude larger acoustic response compared to disturbances in the subsonic stream. Some receptive forcing inputs do not generate significant acoustic waves, which may guide excitation with low noise impact.

physics.flu-dyn↗

arXiv2024

Re-examination of the role of displacement and photon catalysis operation in continuous variable measurement device-independent quantum key distribution

We investigate the benefits of using $m$-photon catalysed two-mode squeezed coherent ($m$-PCTMSC) state in continuous variable measurement device-independent quantum key distribution (CV-MDI-QKD). To that end, we derive the Wigner characteristic function of the $m$-PCTMSC state and show that the 0-PCTMSC state is a Gaussian state and is an inferior choice as compared to the zero photon catalyzed two-mode squeezed vacuum state for CV-MDI-QKD. We carry out the optimization of the secret key rate with respect to all state parameters, namely variance, transmissivity, and displacement. Contrary to many recent proposals, the results show that zero- and single-photon catalysis operation provides only a marginal benefit in improving the maximum transmission distance. Secondly, we find that displacement offers no benefit in improving CV-MDI-QKD.

quant-ph↗

arXiv2024

Optimization of state parameters in displacement assisted photon subtracted measurement-device-independent quantum key distribution

Non-Gaussian operations, in particular, photon subtraction (PS), have been shown to enhance the performance of various quantum information processing tasks including continuous variable measurement device independent quantum key distribution (CV-MDI-QKD). This work investigates the role of non-Gaussian resource states, namely, the photon subtracted two-mode squeezed coherent (PSTMSC) (which include photon subtracted two-mode squeezed vacuum (PSTMSV) as a special case) states in CV-MDI-QKD. To this end, we derive the Wigner characteristic function for the resource states, from which the covariance matrix and, finally, the secret key rate expressions are extracted. The optimization of the state parameters is undertaken to find the most suitable resource states in this family of states. There have been previous studies on the PSTMSV and PSTMSC states in CV-MDI-QKD that make use of PS operation. We evaluate such proposals and find to our surprise that both PSTMSC and PSTMSV resource states underperform as compared to the TMSV state rendering PS operation and displacement undesirable.

quant-ph↗

arXiv2024

No real advantage of photon subtraction and displacement in continuous variable measurement device independent quantum key distribution

We critically analyse the role of single photon subtraction (SPS) and displacement in improving the performance of continuous variable measurement device independent quantum key distribution (CV-MDI-QKD). We consider CV-MDI-QKD with resource states generated by SPS on a displaced two-mode squeezed vacuum state. Optimizing the secret key rate with state parameters reveals that implementing SPS yields no benefits in improving the loss tolerance of CV-MDI-QKD. Additionally, we find that displacement too is not useful in improving the performance of CV-MDI-QKD. While our result is in contradistinction with the widely held belief in the field regarding the utility of SPS and displacement in CV-MDI-QKD, it also calls for a re-examination of the role of non-Gaussian operations in increasing the efficiency of various quantum information processing protocols.

quant-ph↗

arXiv2024

Platinum-based Catalysts for Oxygen Reduction Reaction simulated with a Quantum Computer

Hydrogen has emerged as a promising energy source, holding the key to achieve low-carbon and sustainable mobility. However, its applications are still limited by modest conversion efficiency in the electrocatalytic oxygen reduction reaction (ORR) within fuel cells. Consequently, the development of novel catalysts and a profound understanding of the underlying reactions have become of paramount importance. The complex nature of the ORR potential energy landscape and the presence of strong electronic correlations present challenges to atomistic modelling using classical computers. This scenario opens new avenues for the implementation of novel quantum computing workflows to address these molecular systems. Here, we present a pioneering study that combines classical and quantum computational approaches to investigate the ORR on pure platinum and platinum/cobalt surfaces. Our research demonstrates, for the first time, the feasibility of implementing this workflow on the H1-series trapped-ion quantum computer and identify the challenges of the quantum chemistry modelling of this reaction. The results highlight the involvement of strongly correlated species in the cobalt-containing catalyst, suggesting their potential as ideal candidates for showcasing quantum advantage in future applications.

quant-ph↗

arXiv2024

Classical and quantum cost of measurement strategies for quantum-enhanced auxiliary field Quantum Monte Carlo

Quantum-enhanced auxiliary field quantum Monte Carlo (QC-AFQMC) uses output from a quantum computer to increase the accuracy of its classical counterpart. The algorithm requires the estimation of overlaps between walker states and a trial wavefunction prepared on the quantum computer. We study the applicability of this algorithm in terms of the number of measurements required from the quantum computer and the classical costs of post-processing those measurements. We compare the classical post-processing costs of state-of-the-art measurement schemes using classical shadows to determine the overlaps and argue that the overall post-processing cost stemming from overlap estimations scales like $\mathcal{O}(N^9)$ per walker throughout the algorithm. With further numerical simulations, we compare the variance behavior of the classical shadows when randomizing over different ensembles, e.g., Cliffords and (particle-number restricted) matchgates beyond their respective bounds, and uncover the existence of covariances between overlap estimations of the AFQMC walkers at different imaginary time steps. Moreover, we include analyses of how the error in the overlap estimation propagates into the AFQMC energy and discuss its scaling when increasing the system size.

quant-ph↗

arXiv2024

Learn and Search: An Elegant Technique for Object Lookup using Contrastive Learning

The rapid proliferation of digital content and the ever-growing need for precise object recognition and segmentation have driven the advancement of cutting-edge techniques in the field of object classification and segmentation. This paper introduces "Learn and Search", a novel approach for object lookup that leverages the power of contrastive learning to enhance the efficiency and effectiveness of retrieval systems. In this study, we present an elegant and innovative methodology that integrates deep learning principles and contrastive learning to tackle the challenges of object search. Our extensive experimentation reveals compelling results, with "Learn and Search" achieving superior Similarity Grid Accuracy, showcasing its efficacy in discerning regions of utmost similarity within an image relative to a cropped image. The seamless fusion of deep learning and contrastive learning to address the intricacies of object identification not only promises transformative applications in image recognition, recommendation systems, and content tagging but also revolutionizes content-based search and retrieval. The amalgamation of these techniques, as exemplified by "Learn and Search," represents a significant stride in the ongoing evolution of methodologies in the dynamic realm of object classification and segmentation.

cs.CV↗

arXiv2024

Non-Gaussian two mode squeezed thermal states in continuous variable quantum teleportation

While photon catalyzed two mode squeezed vacuum state has been considered in context of quantum teleportation, similar studies have not been yet conducted for photon catalyzed two-mode squeezed thermal (TMST) state. This can be attributed to challenges involved in the evaluation of teleportation fidelity for photon catalyzed TMST state. In this article, we consider a practical scheme for the implementation of non-Gaussian operation, viz., photon subtraction, photon addition, and photon catalysis, on TMST state. The generated states are employed as resources in continuous-variable quantum teleportation. The results show that the three non-Gaussian operations can enhance the teleportation fidelity. Considering the success probability of the non-Gaussian operations, we identify single-photon catalysis and single photon subtraction to be optimal for teleporting input coherent states, at low and intermediate squeezing levels.

quant-ph↗

arXiv2024

Unsupervised learning based object detection using Contrastive Learning

Training image-based object detectors presents formidable challenges, as it entails not only the complexities of object detection but also the added intricacies of precisely localizing objects within potentially diverse and noisy environments. However, the collection of imagery itself can often be straightforward; for instance, cameras mounted in vehicles can effortlessly capture vast amounts of data in various real-world scenarios. In light of this, we introduce a groundbreaking method for training single-stage object detectors through unsupervised/self-supervised learning. Our state-of-the-art approach has the potential to revolutionize the labeling process, substantially reducing the time and cost associated with manual annotation. Furthermore, it paves the way for previously unattainable research opportunities, particularly for large, diverse, and challenging datasets lacking extensive labels. In contrast to prevalent unsupervised learning methods that primarily target classification tasks, our approach takes on the unique challenge of object detection. We pioneer the concept of intra-image contrastive learning alongside inter-image counterparts, enabling the acquisition of crucial location information essential for object detection. The method adeptly learns and represents this location information, yielding informative heatmaps. Our results showcase an outstanding accuracy of \textbf{89.2\%}, marking a significant breakthrough of approximately \textbf{15x} over random initialization in the realm of unsupervised object detection within the field of computer vision.

cs.CV↗

arXiv2024

Evaluating Ground State Energies of Chemical Systems with Low-Depth Quantum Circuits and High Accuracy

Solving electronic structure problems is considered one of the most promising applications of quantum computing. However, due to limitations imposed by the coherence time of qubits in the Noisy Intermediate Scale Quantum (NISQ) era or the capabilities of early fault-tolerant quantum devices, it is vital to design algorithms with low-depth circuits. In this work, we develop an enhanced Variational Quantum Eigensolver (VQE) ansatz based on the Qubit Coupled Cluster (QCC) approach, which demands optimization over only $n$ parameters rather than the usual $n+2m$ parameters, where $n$ represents the number of Pauli string time evolution gates $e^{-itP}$, and $m$ is the number of qubits involved. We evaluate the ground state energies of $\mathrm{O_3}$, $\mathrm{Li_4}$, and $\mathrm{Cr_2}$, using CAS(2,2), (4,4) and (6,6) respectively in conjunction with our enhanced QCC ansatz, UCCSD (Unitary Coupled Cluster Single Double) ansatz, and canonical CCSD method as the active space solver, and compare with CASCI results. Finally, we assess our enhanced QCC ansatz on two distinct quantum hardware, IBM Kolkata and Quantinuum H1-1.

quant-ph↗

arXiv2023

Optimal non-Gaussian operations in difference-intensity detection and parity detection-based Mach-Zehnder interferometer

We investigate the benefits of probabilistic non-Gaussian operations in phase estimation using difference-intensity and parity detection-based Mach-Zehnder interferometers (MZI). We consider an experimentally implementable model to perform three different non-Gaussian operations, namely photon subtraction (PS), photon addition (PA), and photon catalysis (PC) on a single-mode squeezed vacuum (SSV) state. In difference-intensity detection-based MZI, two PC operation is found to be the most optimal, while for parity detection-based MZI, two PA operation emerges as the most optimal process. We have also provided the corresponding squeezing and transmissivity parameters at best performance, making our study relevant for experimentalists. Further, we have derived the general expression of moment-generating function, which shall be useful in exploring other detection schemes such as homodyne detection and quadratic homodyne detection.

quant-ph↗

arXiv2023

Advantage of probabilistic non-Gaussian operations in the distillation of single mode squeezed vacuum state

We consider the distillation of squeezing in single mode squeezed vacuum state using three different probabilistic non-Gaussian operations: photon subtraction (PS), photon addition (PA) and photon catalysis (PC). To accomplish this, we consider a practical model to implement these non-Gaussian operations and derive the Wigner characteristic function of the resulting non-Gaussian states. Our result shows that while PS and PC operations can distill squeezing, PA operations cannot. Furthermore, we delve into the success probabilities associated with these non-Gaussian operations and identify optimal parameters for the distillation of squeezing. Our current analysis holds significant relevance for experimental endeavors concerned with squeezing distillation.

quant-ph↗

arXiv2023

Origin of electrical noise near charge neutrality in dual gated graphene device

This letter investigates low frequency 1/ f noise in hBN encapsulated graphene device in a dual gated geometry. The noise study is performed as a function of top gate carrier density (nT G) at different back gate densities (nBG). The noise at low nBG is found to be independent of top gate carrier density. With increasing nBG, noise value increases and a noise peak is observed near charge inhomogeneity of the device. Further increase in nBG leads to decrease in noise magnitude. The shape of the noise is found to be closely related to charge inhomogeneity region of the device. Moreover, the noise and conductivity data near charge neutrality shows clear evidence of noise emanating from combination of charge number and mobility fluctuation

cond-mat.mes-hall↗

arXiv2023

Pragmatic Comparison Analysis of Alternative Option Pricing Models

In this paper, we price European Call three different option pricing models, where the volatility is dynamically changing i.e. non constant. In stochastic volatility (SV) models for option pricing a closed form approximation technique is used, indicating that these models are computationally efficient and have the same level of performance as existing ones. We show that the calibration of SV models, such as Heston model and the High Order Moment based Stochastic Volatility (MSV) is often faster and easier. On 15 different datasets of index options, we show that models which incorporates stochastic volatility achieves accuracy comparable with the existing models. Further, we compare the In Sample and Out Sample pricing errors of each model on each date. Lastly, the pricing of models is compared among three different market to check model performance in different markets. Keywords: Option Pricing Model, Simulations, Index Options, Stochastic Volatility Models, Loss Function http://www.sci-int.com/pdf/638279543859822650.pdf

q-fin.PR↗

arXiv2023

Quantum-enhanced quantum Monte Carlo: an industrial view

In this work, we test a recently developed method to enhance classical auxiliary-field quantum Monte Carlo (AFQMC) calculations with quantum computers against examples from chemistry and material science, representatives of classes of industry-relevant systems. As molecular test cases, we calculate the energy curve of H4 and relative energies of ozone and singlet molecular oxygen with respect to triplet molecular oxygen, which are industrially relevant in organic oxidation reactions. We find that trial wave functions beyond single Slater determinants improve the performance of AFQMC and allow to generate energies close to chemical accuracy compared to full configuration interaction (FCI) or experimental results. As a representative for material science we study a quasi-1D Fermi-Hubbard model derived from CuBr2, a compound displaying electronic structure properties analogous to cuprates. We find that trial wave functions with both, significantly larger fidelities and lower energies over a Hartree-Fock solution, do not necessarily lead to better AFQMC results.

quant-ph↗

arXiv2023

Continuous variable quantum teleportation in a dissipative environment: Comparison of non-Gaussian operations before and after noisy channel

We explore the relative advantages in continuous-variable quantum teleportation when non-Gaussian operations, namely, photon subtraction, addition, and catalysis, are performed before and after interaction with a noisy channel. We generate the resource state for teleporting unknown coherent and squeezed vacuum states using two distinct strategies: (i) Implementation of non-Gaussian operations on TMSV state before interaction with a noisy channel, (ii) Implementation of non-Gaussian operations after interaction of TMSV state with a noisy channel. The results show that either of the two strategies could be more beneficial than the other depending on the type of the non-Gaussian operation, the initial squeezing of the TMSV state, and the parameters characterizing the noisy channel. This strategy can be utilized to effectively improve the efficiency of various non-Gaussian continuous variable quantum information processing tasks in a dissipative environment.

quant-ph↗