arXiv subjects

Subrata Das

Publications and source records attributed to Subrata Das.

At least 19 recordsLinked to original sources

arXiv2026

Mass-anisotropy driven stripe pattern formation and directional modulational instability in polariton condensate

Motivated by recent experimental advances toward electrical control of the effective mass and the realization of anisotropic mass distributions, we investigate the impact of mass anisotropy on driven-dissipative polariton condensates, focusing on modulational instability, pattern formation, and the collective dynamics of the emergent patterns. We show that unequal effective masses along the two orthogonal directions induce stripe pattern formation in an exciton-polariton condensate pumped by a non-resonant Gaussian laser beam above a critical mass ratio. A Bogoliubov analysis of the homogeneously pumped system reveals that mass anisotropy leaves the modulational-instability criteria unchanged but reshapes the unstable-mode dispersion by reducing the most unstable wave- length along the direction of larger effective mass with increasing mass ratio. This introduces an anisotropy-controlled length scale for pattern selection. When the pump width becomes comparable to the most unstable wavelength, the condensate becomes modulationally unstable and develops stripe patterns along the direction of larger effective mass, accompanied by particle-number fluctua- tions and center-of-mass oscillations along the same direction. As the pump width increases further, the stripes become distorted and develop spatial irregularities during the time evolution, indicative of modulational instability. Nevertheless, the anisotropic mass distribution preserves a pronounced directional preference, in contrast to the fully disordered patterns observed in the isotropic-mass case. Our results identify mass anisotropy as a key control parameter for directional modulational instability and pattern formation in nonequilibrium polariton condensates.

cond-mat.quant-gas↗

arXiv2025

A Graph-Based Forensic Framework for Inferring Hardware Noise of Cloud Quantum Backend

Cloud quantum platforms give users access to many backends with different qubit technologies, coupling layouts, and noise levels. The execution of a circuit, however, depends on internal allocation and routing policies that are not observable to the user. A provider may redirect jobs to more error-prone regions to conserve resources, balance load or for other opaque reasons, causing degradation in fidelity while still presenting stale or averaged calibration data. This lack of transparency creates a security gap: users cannot verify whether their circuits were executed on the hardware for which they were charged. Forensic methods that infer backend behavior from user-visible artifacts are therefore becoming essential. In this work, we introduce a Graph Neural Network (GNN)-based forensic framework that predicts per-qubit and per-qubit link error rates of an unseen backend using only topology information and aggregated features extracted from transpiled circuits. We construct a dataset from several IBM 27-qubit devices, merge static calibration features with dynamic transpilation features and train separate GNN regressors for one- and two-qubit errors. At inference time, the model operates without access to calibration data from the target backend and reconstructs a complete error map from the features available to the user. Our results on the target backend show accurate recovery of backend error rate, with an average mismatch of approximately 22% for single-qubit errors and 18% for qubit-link errors. The model also exhibits strong ranking agreement, with the ordering induced by predicted error values closely matching that of the actual calibration errors, as reflected by high Spearman correlation. The framework consistently identifies weak links and high-noise qubits and remains robust under realistic temporal noise drift.

quant-ph↗

arXiv2025

Quantum Hall correlations in tilted extended Bose-Hubbard chains

We demonstrate characteristics of a bosonic fractional quantum Hall (FQH) state in a one-dimensional extended Bose-Hubbard model (eBHM) with a static tilt. In the large tilt limit, quenched kinetic energy leads to emergent dipole moment conservation, enabling mapping to a model generating FQH states. Using exact diagonalization, density matrix renormalization group, and an analytical transfer matrix approach, we analyze energy and entanglement properties to reveal FQH correlations. Our findings set the stage for the use of quenched kinetics in simple time-reversal invariant eBHMs to explore emergent phenomena.

cond-mat.quant-gas↗

arXiv2025

Optimization of Quantum Error Correcting Code under Temporal Variation of Qubit Quality

Error rates in current noisy quantum hardware are not static; they vary over time and across qubits. This temporal and spatial variation challenges the effectiveness of fixed-distance quantum error correction (QEC) codes. In this paper, we analyze 12 days of calibration data from IBM's 127-qubit device (ibm_kyiv), showing the fluctuation of Pauli-X and CNOT gate error rates. We demonstrate that fixed-distance QEC can either underperform or lead to excessive overhead, depending on the selected qubit and the error rate of the day. We then propose a simple adaptive QEC approach that selects an appropriate code distance per qubit, based on daily error rates. Using logical error rate modeling, we identify qubits that cannot be used and qubits that can be recovered with minimal resources. Our method avoids unnecessary resource overhead by excluding outlier qubits and tailoring code distances. Across 12 calibration days on ibm_kyiv, our adaptive strategy reduces physical qubit overhead by over 50% per logical qubit while maintaining access to 85-100% of usable qubits. To further validate the method, we repeat the experiment on two additional 127-qubit devices, ibm_brisbane and ibm_sherbrooke, where the overhead savings reach up to 71% while still preserving over 80% qubit usability. This approach offers a practical and efficient path forward for Noisy Intermediate-Scale Quantum (NISQ)-era QEC strategies.

quant-ph↗

arXiv2025

Impact of Error Rate Misreporting on Resource Allocation in Multi-tenant Quantum Computing and Defense

Cloud-based quantum service providers allow multiple users to run programs on shared hardware concurrently to maximize resource utilization and minimize operational costs. This multi-tenant computing (MTC) model relies on the error parameters of the hardware for fair qubit allocation and scheduling, as error-prone qubits can degrade computational accuracy asymmetrically for users sharing the hardware. To maintain low error rates, quantum providers perform periodic hardware calibration, often relying on third-party calibration services. If an adversary within this calibration service misreports error rates, the allocator can be misled into making suboptimal decisions even when the physical hardware remains unchanged. We demonstrate such an attack model in which an adversary strategically misreports qubit error rates to reduce hardware throughput, and probability of successful trial (PST) for two previously proposed allocation frameworks, i.e. Greedy and Community-Based Dynamic Allocation Partitioning (COMDAP). Experimental results show that adversarial misreporting increases execution latency by 24% and reduces PST by 7.8%. We also propose to identify inconsistencies in reported error rates by analyzing statistical deviations in error rates across calibration cycles.

quant-ph↗

arXiv2024

Unveiling Supersolid Order via Vortex Trajectory Correlations

The task of experimentally investigating the inherently dual properties of a supersolid, a simultaneous superfluid and solid, has become more critical following the recent experimental exploration of supersolid regimes in dipolar Bose-Einstein condensates (BECs) of $^{164}\text{Dy}$. We introduce a supersolid order parameter that uses vortex-vortex trajectory correlations to simultaneously reveal the periodic density of the underlying solid and superfluidity in a single measure. We propose experiments using existing technology to optically create and image trajectories of vortex dipoles in dipolar BECs that is applicable to large system sizes. We numerically test our observable and find that vortex-vortex correlations reveal the supersolid lattice structure while distinguishing it from superfluidity even in the presence of dissipation. Our method sets the stage for experiments to use vortex trajectory correlations to investigate fundamental properties of supersolids arising from their dynamics and phase transitions as experimental system sizes are increased.

cond-mat.quant-gas↗

arXiv2024

Investigating impact of bit-flip errors in control electronics on quantum computation

In this paper, we investigate the impact of bit flip errors in FPGA memories in control electronics on quantum computing systems. FPGA memories are integral in storing the amplitude and phase information pulse envelopes, which are essential for generating quantum gate pulses. However, these memories can incur faults due to physical and environmental stressors such as electromagnetic interference, power fluctuations, and temperature variations and adversarial fault injections, potentially leading to errors in quantum gate operations. To understand how these faults affect quantum computations, we conducted a series of experiments to introduce bit flips into the amplitude (both real and imaginary components) and phase values of quantum pulses using IBM's simulated quantum environments, FakeValencia, FakeManila, and FakeLima. Our findings reveal that bit flips in the exponent and initial mantissa bits of the real amplitude cause substantial deviations in quantum gate operations, with TVD increases as high as ~200%. Interestingly, the remaining bits exhibited natural tolerance to errors. We proposed a 3-bit repetition error correction code, which effectively reduced the TVD increases to below 40% without incurring any memory overhead. Due to reuse of less significant bits for error correction, the proposed approach introduces maximum of 5-7% extra TVD in nominal cases. However, this can be avoided by sacrificing memory area for implementing the repetition code.

quant-ph↗

arXiv2024

Lattice Surgery for Dummies

Quantum error correction (QEC) plays a crucial role in correcting noise and paving the way for fault-tolerant quantum computing. This field has seen significant advancements, with new quantum error correction codes emerging regularly to address errors effectively. Among these, topological codes, particularly surface codes, stand out for their low error thresholds and feasibility for implementation in large-scale quantum computers. However, these codes are restricted to encoding a single qubit. Lattice surgery is crucial for enabling interactions among multiple encoded qubits or between the lattices of a surface code, ensuring that its sophisticated error-correcting features are maintained without significantly increasing the operational overhead. Lattice surgery is pivotal for scaling QECCs across more extensive quantum systems. Despite its critical importance, comprehending lattice surgery is challenging due to its inherent complexity, demanding a deep understanding of intricate quantum physics and mathematical concepts. This paper endeavors to demystify lattice surgery, making it accessible to those without a profound background in quantum physics or mathematics. This work explores surface codes, introduces the basics of lattice surgery, and demonstrates its application in building quantum gates and emulating multi-qubit circuits.

quant-ph↗

arXiv2024

Induced supersolidity and hypersonic flow of a dipolar Bose-Einstein Condensate in a rotating bubble trap

Motivated by the recent realization of space-borne Bose-Einstein Condensates (BECs) under micro-gravity conditions, we extend the understanding of ultracold dipolar bosonic gases by exploring their behavior in a novel trapping configuration known as the ``bubble trap" topology. Utilizing the three-dimensional numerical simulations within the extended Gross-Pitaevskii framework, we unveil diverse ground state phases in this static curved topology. Subsequently, we investigate the influence of rotation on a dipolar BEC confined to the surface of a spherical bubble. Our findings reveal that the rotation of a bubble trap at certain rotation frequencies can modify the effective local dipole-dipole interaction strength, leading to the induction of supersolidity and the formation of quantum droplets. In addition, we demonstrate that a bubble trap can sustain high circulation, with the flow persisting for a longer time. Significantly, adjusting the rf detuning parameter allows the condensate to achieve hypersonic velocity. Finally, we also explore the impact of drastic change in the topological nature of the trap on the rotating dipolar BEC, transitioning from a filled shell trap to a bubble trap and vice versa. Based on the results of the topological transition, we propose a dynamic protocol to drive the interacting atomic gas into the quantum Hall regime.

cond-mat.quant-gas↗

arXiv2024

Sinusoidal magnetic field induced topological excitations in a spin-orbit coupled spinor condensate

We explore topological excitations in a spin-1 Bose-Einstein condensate subjected to an in-plane sinusoidally varying magnetic field and Rashba spin-orbit coupling (SOC). In the absence of SOC, the periodic magnetic field induces vortex-anti-vortex structures in the $\ket{F=1, m_F=\pm1}$ condensates at saddle-points, such that the net topological charge remains zero. The introduction of Rashba SOC breaks the system's symmetry, leading to non-conservation of overall angular momentum in the spin-1 condensate. This anisotropy results in the emergence of certain skyrmion spin textures. We provide a comparative study for various in-plane magnetic field configurations while keeping the SOC strength constant. Our numerical simulations within the mean-field framework reveal the potential to engineer diverse topological excitations controlled by the interplay between spin-orbit coupling and in-plane magnetic field in a spinor condensate.

cond-mat.quant-gas↗

arXiv2024

Hardware Trojans in Quantum Circuits, Their Impacts, and Defense

The reliability of the outcome of a quantum circuit in near-term noisy quantum computers depends on the gate count and depth for a given problem. Circuits with a short depth and lower gate count can yield the correct solution more often than the variant with a higher gate count and depth. To work successfully for Noisy Intermediate Scale Quantum (NISQ) computers, quantum circuits need to be optimized efficiently using a compiler that decomposes high-level gates to native gates of the hardware. Many 3rd party compilers are being developed for lower compilation time, reduced circuit depth, and lower gate count for large quantum circuits. Such compilers, or even a specific release version of a compiler that is otherwise trustworthy, may be unreliable and give rise to security risks such as insertion of a quantum trojan during compilation that evades detection due to the lack of a golden/Oracle model in quantum computing. Trojans may corrupt the functionality to give flipped probabilities of basis states, or result in a lower probability of correct basis states in the output. In this paper, we investigate and discuss the impact of a single qubit Trojan (we have chosen a Hadamard gate and a NOT gate) inserted one at a time at various locations in benchmark quantum circuits without changing the the depth of the circuit. Results indicate an average of 16.18% degradation for the Hadamard Trojan without noise, and 7.78% with noise. For the NOT Trojan (with noise) there is 14.6% degradation over all possible inputs. We then discuss the detection of such Trojans in a quantum circuit using CNN-based classifier achieving an accuracy of 90%.

cs.CR↗

arXiv2023

Induced supersolidity in a Dy-Er mixture

Recent experimental realization of the heteronuclear dipolar mixture of Dy and Er atoms opens fascinating prospects for creating intriguing novel phases in dipolar quantum gases. The experimentally measured value of intra-species $s$-wave scattering length of $^{166}$Er condensate in a $^{164}$Dy-$^{166}$Er mixture is larger than its intra-species dipolar length, implies that the $^{166}$Er condensate itself will not be in a regime of dominated dipole-dipole interaction (DDI). However, we find that the presence of $^{164}$Dy atoms with high magnetic moment induces droplet nucleation and supersolidity in $^{166}$Er condensate via the long-range and anisotropic inter-species DDI. Remarkably, we find that the imbalance in the magnetic dipole moment combined with its strong anisotropic coupling led to the emergence of unique ground state phases. The emerging phases include doubly superfluid states, a mixture of insulating droplets and supersolid states, binary supersolids with uniform and alternating domains and a combination of supersolid-superfluid mixed states. We delineate the properties of all these ground state phases and construct a phase diagram. We also explore the dynamical evolution across these phase boundaries via a linear quench of inter-species scattering length. Although we have demonstrated the result for the $^{164}$Dy-$^{166}$Er mixture, our results are generally valid for other dipolar bosonic mixtures of different Dy-Er isotope combinations and may become an important benchmark for future experimental scenarios.

cond-mat.quant-gas↗

arXiv2023

Trojan Taxonomy in Quantum Computing

Quantum computing introduces unfamiliar security vulnerabilities demanding customized threat models. Hardware and software Trojans pose serious concerns needing rethinking from classical paradigms. This paper develops the first structured taxonomy of Trojans tailored to quantum information systems. We enumerate potential attack vectors across the quantum stack from hardware to software layers. A categorization of quantum Trojan types and payloads is outlined ranging from reliability degradation, functionality corruption, backdoors, and denial-of-service. Adversarial motivations behind quantum Trojans are analyzed. By consolidating diverse threats into a unified perspective, this quantum Trojan taxonomy provides insights guiding threat modeling, risk analysis, detection mechanisms, and security best practices customized for this novel computing paradigm.

cs.CR↗

arXiv2023

Isostructural phase transition in Tb2Ti2O7 under pressure and temperature: Insights from synchrotron X-ray diffraction

Tb2Ti2O7, a pyrochlore system, has garnered significant interest due to its intriguing structural and physical properties and their dependence on external physical parameters. In this study, utilizing high-brilliance synchrotron X-ray diffraction, we conducted a comprehensive investigation of structural evolution of Tb2Ti2O7 under external pressure and temperature. We have conclusively confirmed the occurrence of an isostructural phase transition beyond the pressure of 10 GPa. The transition exhibits a distinct signature in the variation of lattice parameters under pressure and leads to changes in mechanical properties. The underlying physics driving this transition can be understood in terms of localized rearrangement of atoms while retaining the overall cubic symmetry of the crystal. Notably, the observed transition remains almost independent of temperature. Our findings provide insights into the distinctive behaviour of the isostructural phase transition in Tb2Ti2O7.

cond-mat.mtrl-sci↗

arXiv2023

A First Order Survey of Quantum Supply Dynamics and Threat Landscapes

Quantum computing, with its transformative computational potential, is gaining prominence in the technological landscape. As a new and exotic technology, quantum computers involve innumerable Intellectual Property (IP) in the form of fabrication recipe, control electronics and software techniques, to name a few. Furthermore, complexity of quantum systems necessitates extensive involvement of third party tools, equipment and services which could risk the IPs and the Quality of Service and enable other attack surfaces. This paper is a first attempt to explore the quantum computing ecosystem, from the fabrication of quantum processors to the development of specialized software tools and hardware components, from a security perspective. By investigating the publicly disclosed information from industry front runners like IBM, Google, Honeywell and more, we piece together various components of quantum computing supply chain. We also uncover some potential vulnerabilities and attack models and suggest defenses. We highlight the need to scrutinize the quantum computing supply chain further through the lens of security.

quant-ph↗

arXiv2023

Q-Pandora Unboxed: Characterizing Noise Resilience of Quantum Error Correction Codes

Quantum error correction codes (QECCs) are critical for realizing reliable quantum computing by protecting fragile quantum states against noise and errors. However, limited research has analyzed the noise resilience of QECCs to help select optimal codes. This paper conducts a comprehensive study analyzing two QECCs - rotated and unrotated surface codes - under different error types and noise models using simulations. Among them, rotated surface codes perform best with higher thresholds attributed to simplicity and lower qubit overhead. The noise threshold, or the point at which QECCs become ineffective, surpasses the error rate found in contemporary quantum processors. When confronting quantum hardware where a specific error or noise model is dominant, a discernible hierarchy emerges for surface code implementation in terms of resource demand. This ordering is consistently observed across unrotated, and rotated surface codes. Our noise model analysis ranks the code-capacity model as the most pessimistic and circuit-level model as the most realistic. The study maps error thresholds, revealing surface code's advantage over modern quantum processors. It also shows higher code distances and rounds consistently improve performance. However, excessive distances needlessly increase qubit overhead. By matching target logical error rates and feasible number of qubits to optimal surface code parameters, our study demonstrates the necessity of tailoring these codes to balance reliability and qubit resources. Conclusively, we underscore the significance of addressing the notable challenges associated with surface code overheads and qubit improvements.

quant-ph↗

arXiv2023

TrojanNet: Detecting Trojans in Quantum Circuits using Machine Learning

Quantum computing holds tremendous potential for various applications, but its security remains a crucial concern. Quantum circuits need high-quality compilers to optimize the depth and gate count to boost the success probability on current noisy quantum computers. There is a rise of efficient but unreliable/untrusted compilers; however, they present a risk of tampering such as Trojan insertion. We propose TrojanNet, a novel approach to enhance the security of quantum circuits by detecting and classifying Trojan-inserted circuits. In particular, we focus on the Quantum Approximate Optimization Algorithm (QAOA) circuit that is popular in solving a wide range of optimization problems. We investigate the impact of Trojan insertion on QAOA circuits and develop a Convolutional Neural Network (CNN) model, referred to as TrojanNet, to identify their presence accurately. Using the Qiskit framework, we generate 12 diverse datasets by introducing variations in Trojan gate types, the number of gates, insertion locations, and compiler backends. These datasets consist of both original Trojan-free QAOA circuits and their corresponding Trojan-inserted counterparts. The generated datasets are then utilized for training and evaluating the TrojanNet model. Experimental results showcase an average accuracy of 98.80% and an average F1-score of 98.53% in effectively detecting and classifying Trojan-inserted QAOA circuits. Finally, we conduct a performance comparison between TrojanNet and existing machine learning-based Trojan detection methods specifically designed for conventional netlists.

quant-ph↗

arXiv2023

Randomized Reversible Gate-Based Obfuscation for Secured Compilation of Quantum Circuit

The success of quantum circuits in providing reliable outcomes for a given problem depends on the gate count and depth in near-term noisy quantum computers. Quantum circuit compilers that decompose high-level gates to native gates of the hardware and optimize the circuit play a key role in quantum computing. However, the quality and time complexity of the optimization process can vary significantly especially for practically relevant large-scale quantum circuits. As a result, third-party (often less-trusted/untrusted) compilers have emerged, claiming to provide better and faster optimization of complex quantum circuits than so-called trusted compilers. However, untrusted compilers can pose severe security risks, such as the theft of sensitive intellectual property (IP) embedded within the quantum circuit. We propose an obfuscation technique for quantum circuits using randomized reversible gates to protect them from such attacks during compilation. The idea is to insert a small random circuit into the original circuit and send it to the untrusted compiler. Since the circuit function is corrupted, the adversary may get incorrect IP. However, the user may also get incorrect output post-compilation. To circumvent this issue, we concatenate the inverse of the random circuit in the compiled circuit to recover the original functionality. We demonstrate the practicality of our method by conducting exhaustive experiments on a set of benchmark circuits and measuring the quality of obfuscation by calculating the Total Variation Distance (TVD) metric. Our method achieves TVD of up to 1.92 and performs at least 2X better than a previously reported obfuscation method. We also propose a novel adversarial reverse engineering (RE) approach and show that the proposed obfuscation is resilient against RE attacks. The proposed technique introduces minimal degradation in fidelity (~1% to ~3% on average).

quant-ph↗