arXiv subjects

Kavita Dorai

Publications and source records attributed to Kavita Dorai.

At least 19 recordsLinked to original sources

arXiv2026

Neural networks learn to reconstruct multipartite entanglement from quantum marginals

Different sets of local correlations are not equivalent: some fragments of reduced data uniquely determine a global quantum state, while others leave it ambiguous. The quantum marginal problem asks whether a collection of reduced density matrices uniquely determines a compatible global quantum state. Although generic quantum states are uniquely specified by suitable sets of marginals, different collections of marginals are not equally informative: some uniquely determine the global state, whereas others leave it ambiguous. Identifying when uniqueness holds, and reconstructing the global state from partial information, remains computationally demanding and experimentally challenging. We show that information about the multipartite entanglement class and reconstructability in four-qubit systems is compactly encoded in small sets of two- and three-qubit marginals. Using semidefinite programming, we chart the reconstructability landscape across 49 inequivalent SLOCC entanglement classes and show that uniqueness strongly depends on both entanglement structure and marginal order. Neural networks trained only on reduced density matrices learn this structure directly. They accurately classify marginal reconstructability and, when uniqueness holds, reconstruct the full four-qubit density matrix with high fidelity from two- and three-qubit marginals. We benchmark the approach on a four-qubit nuclear magnetic resonance quantum processor and demonstrate that reconstructions from experimentally measured marginals remain faithful despite phase damping and control imperfections. Our results show that neural networks can learn when local correlations uniquely specify a global quantum state, and reveal how global quantum structure is encoded in reduced data.

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arXiv2026

Realizing the Petz Recovery Map on an NMR Quantum Processor

The Petz recovery map is a central construct in quantum information theory, providing an explicit, channel-aware prescription for reversing the effects of noise. Unlike standard quantum operations, the Petz map is intrinsically dependent on a chosen reference state, which makes its physical implementation and experimental validation particularly challenging. Here, we report an experimental realization of Petz recovery maps on a nuclear magnetic resonance (NMR) quantum processor using the duality quantum computing (DQC) algorithm. We investigate two paradigmatic single-qubit noise models: amplitude damping and phase damping, and construct corresponding families of Petz recovery maps for varying reference states. By systematically tuning the reference state, we experimentally demonstrate the state-adapted nature of Petz recovery, observing both enhanced recovery when the reference state is well matched and fidelity degradation for mismatched choices. Our experimental results show close quantitative agreement with theoretical predictions, providing direct evidence that the Petz recovery map constitutes a physically realizable, reference-state-dependent recovery channel rather than a purely formal inverse of noise. This work bridges the gap between the abstract information-theoretic formulation of Petz recovery and its implementation on a realistic quantum platform, and establishes an experimental benchmark for testing noise-adapted recovery strategies on near-term quantum devices.

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arXiv2024

Experimental investigation of a quantum Otto heat engine with shortcuts to adiabaticity implemented using counter-adiabatic driving

The finite time operation of a quantum Otto heat engine leads to a trade-off between efficiency and output power, which is due to the deviation of the system from the adiabatic path. This trade-off caveat can be bypassed by using the shortcut-to-adiabaticity protocol. We experimentally implemented a quantum Otto heat engine using spin-1/2 nuclei on a nuclear magnetic resonance (NMR) quantum processor. We investigated its performance using the shortcut-to-adiabaticity technique via counter-adiabatic driving with the inclusion of the cost to perform the shortcut. We use two different metrics that incorporate the cost of shortcut-to-adiabaticity to define engine efficiency and experimentally analyze which one is more appropriate for the NMR platform. We found a significant improvement in the performance of the quantum Otto heat engine driven by shortcut-to-adiabaticity, as compared to the non-adiabatic heat engine.

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arXiv2024

Simulating Three-Flavor Neutrino Oscillations on an NMR Quantum Processor

Neutrino oscillations can be efficiently simulated on a quantum computer using the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) theory in close analogy to the physical processes realized in experiments. We simulate three-flavor neutrino oscillations on a two-qubit NMR quantum information processor. The three-flavor neutrino states were encoded into the two-qubit system, leaving one redundant basis state (representing an unphysical sterile neutrino). We simulated the neutrino oscillations in different scenarios, including propagation in vacuum and through surrounding matter, and both with and without a CP violating phase $δ$ at a Deep Underground Neutrino Experiment (DUNE) baseline distance of L = 1285 km. The oscillation probabilities were obtained after unitarily time evolving the initial flavor state and and comparisons were performed between different scenarios. Further, we design and implement an optimized quantum circuit encoding all four parameters (three mixing angles-$θ_{12},θ_{23},θ_{13}$ and one complex phase $δ$) to implement the PMNS unitary matrix, which relates the flavor and mass eigenstates. The interaction with matter is considered as a perturbation to the vacuum Hamiltonian, and the same quantum circuit is employed with an approximation of two mixing angles ($θ_{12}$ and $θ_{13}$ ) and mass eigenvalues. Our experimental results match well with numerical simulations and highlight the potential of quantum computers for exploring the physics of neutrino oscillations.

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arXiv2024

Experimental investigation of coherence contributions to a nonequilibrium thermodynamic process in a driven quantum system

The work done when a system at thermal equilibrium is externally driven by a unitary control parameter leads to irreversible entropy production. The entropy produced can be thought of as a combination of coherence generation and a population mismatch between the target equilibrium state and the actually achieved final state. We experimentally explored this out-of-equilibrium process in an NMR quantum processor and studied the contribution of coherence to irreversible entropy generation. We verified a generalized Clausius inequality, which affirms that irreversible entropy production is lower-bounded.

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arXiv2024

Entanglement Classification of Arbitrary Three-Qubit States via Artificial Neural Networks

We design and successfully implement artificial neural networks (ANNs) to detect and classify entanglement for three-qubit systems using limited state features. The overall design principle is a feed forward neural network (FFNN), with the output layer consisting of a single neuron for the detection of genuine multipartite entanglement (GME) and six neurons for the classification problem corresponding to six entanglement classes under stochastic local operations and classical communication (SLOCC). The models are trained and validated on a simulated dataset of randomly generated states. We achieve high accuracy, around 98%, for detecting GME as well as for SLOCC classification. Remarkably, we find that feeding only 7 diagonal elements of the density matrix into the ANN results in an accuracy greater than 94% for both the tasks, showcasing the strength of the method in reducing the required input data while maintaining efficient performance. Reducing the feature set makes it easier to apply ANN models for entanglement classification, particularly in resource-constrained environments, without sacrificing accuracy. The performance of the ANN models was further evaluated by introducing white noise into the data set, and the results indicate that the models are robust and are able to well tolerate noise.

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arXiv2024

Evolution of different orders of coherence of a three-qubit system and their protection via dynamical decoupling on an NMR quantum processor

We generate different orders of quantum coherence in a three-qubit NMR system and study their dynamics in the presence of inherent noise. Robust dynamical decoupling (DD) sequences are applied to preserve the different coherence orders. Initially, DD sequences are implemented simultaneously on all three spins, which effectively protects third-order coherence; however, other coherence orders decay rapidly instead of being preserved. The robust DD sequences were suitably modified in order to preserve other coherence orders. These sequences are applied to the two participating qubits that generate each zero and second order coherence, ensuring their effective preservation. In contrast, first-order coherence is preserved more efficiently when DD sequences are applied exclusively on the qubit responsible for generating it. Instead of performing full state tomography, coherence orders are measured directly using single pulses. The robust DD protection schemes are finally applied to successfully protect two-qubit entanglement in three-qubit star states.

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arXiv2024

Using a quantum SWAP engine to experimentally validate thermodynamic uncertainty relations

Thermodynamic uncertainty relations (TURs) arise from the bounds on fluctuations of thermodynamics quantities during a non-equilibrium process and they impose constraints on the corresponding process. We experimentally implement a quantum SWAP engine on a nuclear magnetic resonance setup and demonstrate that a Gibbs thermal state can be prepared in two different ways, either directly from a thermal equilibrium state, or by first initializing the system in a pseudopure state. We show that the quantum SWAP engine can work both as a heat engine and as a refrigerator. Starting from a pseudopure state, we construct the SWAP engine, and investigate the violation of two different TURs, namely a generalized TUR and a tighter, more specific TUR. Our results validate that the generalized TUR is obeyed in all the working regimes of the SWAP engine, while the tighter TUR is violated in certain regimes. ~

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arXiv2024

ANN-Enhanced Detection of Multipartite Entanglement in a Three-Qubit NMR Quantum Processor

We use an artificial neural network (ANN) model to identify the entanglement class of an experimentally generated three-qubit pure state drawn from one of the six inequivalent classes under stochastic local operations and classical communication (SLOCC). The ANN model is also able to detect the presence of genuinely multipartite entanglement (GME) in the state. We apply data science techniques to reduce the dimensionality of the problem, which corresponds to a reduction in the number of required density matrix elements to be computed. The ANN model is first trained on a simulated dataset containing randomly generated states, and is later tested and validated on noisy experimental three-qubit states cast in the canonical form and generated on a nuclear magnetic resonance (NMR) quantum processor. We benchmark the ANN model via Support Vector Machines (SVMs) and K-Nearest Neighbor (KNN) algorithms and compare the results of our ANN-based entanglement classification with existing three-qubit SLOCC entanglement classification schemes such as 3-tangle and correlation tensors. Our results demonstrate that the ANN model can perform GME detection and SLOCC class identification with high accuracy, using a priori knowledge of only a few density matrix elements as inputs. Since the ANN model works well with a reduced input dataset, it is an attractive method for entanglement classification in real-life situations with limited experimental data sets.

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arXiv2024

Experimental decoherence mitigation using a weak measurement-based scheme and the duality quantum algorithm

We experimentally demonstrate a weak measurement and measurement reversal-based scheme to ameliorate the effects of decoherence due to amplitude damping, on an NMR quantum processor. The weak measurement and measurement reversal processes require the implementation of non-unitary operations, which are typically infeasible on conventional quantum processors, where only unitary quantum operations are allowed. The duality quantum algorithm is used to efficiently implement the required non-unitary quantum operations corresponding to weak measurement and measurement reversal. We experimentally validate the efficacy of the weak measurement-based decoherence mitigation scheme by showing state protection on a four-qubit system, with one qubit being designated as the 'system qubit', while the remaining three qubits serve as 'ancilla qubits'. Our experimental results clearly demonstrate the success of the weak measurement-based decoherence mitigation scheme in protecting the desired state. Since the measurement process involved has trace less than unity, the scheme can be thought of as a filtration scheme, where a subset of the spins is protected while the rest of the spins can be discarded.

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arXiv2024

Using linear and nonlinear entanglement witnesses to generate and detect bound entangled states on an IBM quantum processor

We investigate bound entanglement in three-qubit mixed states which are diagonal in the Greenberger-Horne-Zeilinger (GHZ) basis. Entanglement in these states is detected using entanglement witnesses and the analysis focuses on states exhibiting positive partial transpose (PPT). We then compare the detection capabilities of optimal linear and nonlinear entanglement witnesses. In theory, both linear and nonlinear witnesses produce non-negative values for separable states and negative values for some entangled GHZ diagonal states with PPT, indicating the presence of entanglement. Our experimental results reveal that in cases where linear entanglement witnesses fail to detect entanglement, nonlinear witnesses are consistently able to identify its presence. Optimal linear and nonlinear witnesses were generated on an IBM quantum computer and their performance was evaluated using two bound entangled states (Kay and Kye states) from the literature, and randomly generated entangled states in the GHZ diagonal form. Additionally, we propose a general quantum circuit for generating a three-qubit GHZ diagonal mixed state using a six-qubit pure state on the IBM quantum processor. We experimentally implemented the circuit to obtain expectation values for three-qubit mixed states and compute the corresponding entanglement witnesses.

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arXiv2024

Ground and excited state energy calculations of the H2 molecule using a variational quantum eigensolver algorithm on an NMR quantum simulator

Variational quantum algorithms are emerging as promising candidates for near-term practical applications of quantum information processors, in the field of quantum chemistry. We implement the variational quantum eigensolver algorithm to calculate the molecular ground-state energy of the H2 molecule and experimentally demonstrated it on an NMR quantum processor. Further, we simulate the excited states of the H2 molecule using the variational quantum deflation algorithm and experimentally demonstrate it on the same NMR quantum processor. We also develop the first simulation of the energy calculation of the H2 molecule using only a single qubit, and verify the results on an NMR quantum computer. Our experimental results demonstrate that only a single NMR qubit suffices to calculate the molecular energies of the H2 molecule to the desired accuracy.

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arXiv2024

Experimental realization of quantum non-Markovianity through the convex mixing of Pauli semigroups on an NMR quantum processor

This experimental study aims to investigate the convex combinations of Pauli semigroups with arbitrary mixing parameters to determine whether the resulting dynamical map exhibits Markovian or non-Markovian behavior. Specifically, we consider the cases of equal as well as unequal mixing of two Pauli semigroups, and demonstrate that the resulting map is always non-Markovian. Additionally, we study three cases of three-way mixing of the three Pauli semigroups and determine the Markovianity or non-Markovianity of the resulting maps by experimentally determining the decay rates. To simulate the non-unitary dynamics of a single qubit system with different mixing combinations of Pauli semigroups on an NMR quantum processor, we use an algorithm involving two ancillary qubits. The experimental results align with the theoretical predictions.

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arXiv2023

Experimental quantum state transfer of an arbitrary single-qubit state on a cycle with four vertices using a coined quantum random walk

We experimentally demonstrate the transfer of an unknown single-qubit state from Alice to Bob via a two-step discrete-time quantum random walk on a cycle with four vertices on a four-qubit nuclear magnetic resonance quantum processor. The qubits with Alice and Bob are used as coin qubits and the walk is carried out on in a two-qubit `Gaming Arena'. In this scheme, the required entangled state is generated naturally via conditional shift operators during the quantum walk, instead of being prepared in advance. We implement controlled operators at Bob's end, which are controlled by Alice's coin qubit and arena qubits, in order to reconstruct Alice's randomly generated state at Bob's end. To characterize the state transfer process, we perform quantum process tomography by repeating the experiment for a set of input states $\{ \vert 0\rangle, \vert 1\rangle, \vert +\rangle, \vert -\rangle \}$. Using an entanglement witness, we certify that the quantum walk generates a genuine quadripartite entangled state of all four qubits. To evaluate the efficacy of the transfer scheme, We use quantum state tomography to reconstruct the transferred state by calculating the projection of the experimentally reconstructed four-qubit density matrix onto three-qubit basis states. Our results demonstrate that the quantum circuit is able to perform quantum state transfer via the two-step quantum random walk with high fidelity.

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arXiv2023

Neural network assisted quantum state and process tomography using limited data sets

In this study we employ a feed-forward artificial neural network (FFNN) architecture to perform tomography of quantum states and processes obtained from noisy experimental data. To evaluate the performance of the FFNN, we use a heavily reduced data set and show that the density and process matrices of unknown quantum states and processes can be reconstructed with high fidelity. We use the FFNN model to tomograph 100 two-qubit and 128 three-qubit states which were experimentally generated on a nuclear magnetic resonance (NMR) quantum processor. The FFNN model is further used to characterize different quantum processes including two-qubit entangling gates, a shaped pulsed field gradient, intrinsic decoherence processes present in an NMR system, and various two-qubit noise channels (correlated bit flip, correlated phase flip and a combined bit and phase flip). The results obtained via the FFNN model are compared with standard quantum state and process tomography methods and the computed fidelities demonstrates that for all cases, the FFNN model outperforms the standard methods for tomography.

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arXiv2023

State-independent robust heat-bath algorithmic cooling of nuclear spins

In this work, we experimentally demonstrate the implementation of a recently proposed robust and state-independent heat-bath algorithmic cooling (HBAC) method [1] on an NMR quantum processor. While HBAC methods improve the purity of a quantum system via iterative unitary entropy compression, they are difficult to implement experimentally since they use sort operations that are different for each iteration. The new robust HBAC method proved that optimal HBAC is possible without prior state information and using a single fixed operation. We modified the protocol to experimentally perform efficient cooling of 13C and 15N spins and provide an optimal decomposition of this modified protocol in terms of quantum gates. This is the first time that optimal HBAC has been experimentally demonstrated on 15N spins. We examined the relaxation dynamics of these algorithmically cooled spins, in order to ascertain the effect of decoherence on the cooled states.

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arXiv2023

Direct tomography of quantum states and processes via weak measurements of Pauli spin operators on an NMR quantum processor

In this paper, we present an efficient weak measurement-based scheme for direct quantum state tomography (DQST) and direct quantum process tomography (DQPT), and experimentally implement it on an NMR ensemble quantum information processor without involving any projective measurements. We develop a generalized quantum circuit that enables us to directly measure selected elements of the density matrix and process matrix which characterize unknown quantum states and processes, respectively. This generalized quantum circuit uses the scalar J-coupling to control the interaction strength between the system qubits and the metre qubit. We experimentally implement these weak measurement-based DQST and DQPT protocols and use them to accurately characterize several two-qubit quantum states and single-qubit quantum processes. An extra qubit is used as a metre qubit to implement the DQST protocol, while for the DQPT protocol, two extra qubits (one as a metre qubit and the other as an ancilla qubit) are used.

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arXiv2022

Experimental construction of a symmetric three-qubit entangled state and its utility in testing the violation of a Bell inequality on an NMR quantum simulator

We designed a quantum circuit to prepare a permutation-symmetric maximally entangled three-qubit state called the $\vert {\rm S} \rangle$ state and experimentally created it on an NMR quantum processor. The presence of entanglement in the state was certified by computing two different entanglement measures, namely negativity and concurrence. We used the $\vert {\rm S} \rangle$ state in conjunction with a set of maximally incompatible local measurements, to demonstrate the maximal violation of inequality number $26$ in Sliwa's classification scheme, which is a tight Bell inequality for the (3,2,2) scenario i.e. the three party, two measurement settings and two measurement outcomes scenario.

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