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Shraddha Singh

Publications and source records attributed to Shraddha Singh.

At least 19 recordsLinked to original sources

Non-Abelian Quantum Signal Processing: A Composite Pulse for Fast Analytic Control of Hybrid Oscillator-Qubit Processors

Quantum Signal Processing (QSP) transforms a unitary parameterized by a classical variable $θ$ into one governed by a polynomial function $f(θ)$. Though quantum mechanics is linear, such highly nonlinear transformations arise naturally from the curvature of the qubit Bloch sphere. The QSP primitive underpins most quantum algorithms and finds broad utility in robust control by decreasing sensitivity to parameter errors, and in quantum sensing by increasing sensitivity to target parameters. In this work, we extend QSP to a new multivariate class, non-Abelian QSP, that utilizes a set of non-commuting (operator-valued) control parameters $\{\hatθ_1, \hatθ_2, \dots\}$. Experimental instantiations of this richer algebraic structure are currently being explored in hybrid oscillator-qubit systems realized in superconducting and trapped-ion processors, where the non-commuting variables are oscillator positions and momenta. We demonstrate the utility of our construction, the Gaussian-controlled-rotation (GCR) which is a canonical instance of this class, across three domains: fully analytical state preparation circuits whose performance matches state-of-the-art machine-learning protocols for preparing squeezed, cat, GKP, and Fock states; a complete analytical framework for universal control of GKP bosonic error-corrected qubits, including logical readout and error-corrected gate teleportation --with mid-circuit error detection and generalization to arbitrary lattices, qudits, and multi-mode codes uniquely enabled by the analytical structure; and a construction closing a key gap in oscillator-aided quantum phase estimation algorithms. These results establish non-Abelian QSP as a powerful new frontier, one that is not merely of theoretical interest but ready to be put to work in the laboratory today.

quant-ph

Borrowed Identities: Malleable Distillation Factories and a Unified Numerical Search

Magic-state distillation is one of the leading overheads in fault-tolerant quantum computation. Existing methods for finding distillation factories require a transversal gate to act correctly on the entire codespace, a constraint that limits both generality and search efficiency. We introduce a strictly weaker borrowed-identity condition, requiring only that the distillation circuit act as the identity on a single input state. It applies uniformly across all levels of the Clifford hierarchy and unifies, within a single level, factories that distill different magic states -- for example, the $|T\rangle$, $|CS\rangle$, and $|CCZ\rangle$ factories. A brute-force search over borrowed-identity circuits with two-group symmetry recovers, within the search range, all distance-2 factories known from code-construction approaches, including entangled-output and multi-output factories previously outside the scope of any single numerical search. This unification yields parent circuits that encode multiple factories, so the output magic-state type can be chosen at compile time rather than fixed by a hard-coded design. The framework also extends beyond CSS codes, unifying constructions, including synthillation and non-CSS catalytic factories, previously obtained by disparate approaches.

quant-ph

In-Situ Simultaneous Magic State Injection on Arbitrary CSS qLDPC Codes

Quantum low-density parity-check (qLDPC) codes can encode many logical qubits within a single code block at low physical qubit overhead, yet magic state injection into such codes remains largely underexplored. Existing state injection proposals for qLDPC codes predominantly follow an external prepare-and-transfer paradigm, in which raw magic states are prepared outside the target code block and subsequently injected via inter-code operations. We propose the first \emph{in-situ} magic state injection: a scheme in which logical magic states are directly prepared within a qLDPC memory block, only using resources required for syndrome extraction. We show that our scheme is generalizable to any CSS qLDPC code, with examples of circuit-level simulations on the $[[144,12,12]]$ Bivariate Bicycle (BB) code and the $[[225,9,4]]$ Hypergraph Product code. We focus on a regime where correlated injection errors are negligible. In the BB code, this corresponds to a configuration that simultaneously injects four logical $|Y\rangle$ states. Under a uniform depolarizing noise model with physical error rate $10^{-3}$, this achieves an injection error rate of $1.62 \times 10^{-3}$ per logical qubit, while the correlated-error contribution is only $2 \times 10^{-5}$ per logical qubit (about $1\%$ of the injection error rate). Under a hardware-motivated asymmetric noise model where single-qubit gate errors are $10\%$ of two-qubit gate errors, the injection error rate per logical qubit falls to $ 6.7 \times 10^{-4} $, below the error rate ($ 10^{-3} $) of the two-qubit gates used to encode the magic states. Its simplicity allows our scheme to be applied to arbitrary CSS qLDPC codes using only the ancilla qubits native to syndrome extraction, and yield a reduction in space overhead relative to both prepare-and-transfer approaches and surface-code-based magic state injection schemes.

quant-ph

Fold-transversal surface code cultivation

Magic state cultivation is a state-of-the-art protocol to prepare ultra-high fidelity non-Clifford resource states for universal quantum computation. It offers a significant reduction in spacetime overhead compared to traditional magic state distillation techniques. Cultivation protocols involve measuring a transversal logical Clifford operator on an initial small-distance code and then rapidly growing to a larger-distance code. In this work, we present a new cultivation scheme in which we measure the fold-transversal Hadamard of the unrotated surface code, and leverage unitary techniques to grow within the surface code family. Using both stabilizer and state vector simulations we find that this approach achieves the lowest known spacetime overhead for magic state cultivation. Practical implementation of our protocol is best suited to architectures with non-local connectivity, showing the strength of architectures where such connectivity is readily available.

quant-ph

Near-perfect quantum teleportation between continuous and discrete encodings

Quantum teleportation between polarized single-photon and phase-opposite coherent states is studied using a hybrid entangled resource and entangled coherent states. The polarized single-photon qubit represents a discrete-variable (DV) quantum system, whereas the phase-opposite coherent-state qubit constitutes a continuous-variable (CV) system. While teleportation from CV to DV can be achieved with near-unit success probability, the reverse process is usually limited to a maximum success probability of $1/2$. We demonstrate that, by employing cross-Kerr nonlinearity together with passive linear optical components such as polarizing beam splitters, beam splitters, and phase shifters, almost perfect teleportation from DV to CV encodings can also be achieved.

quant-ph

The Zubarev Double Time Greens function-A Vintage Many Body Technique

These lecture notes present a comprehensive and powerful many-body technique pioneered in 1960 by D. N. Zubarev. The technique, known as the Zubarev Double Time Greens Function method, was used extensively by leading solid state physicists such as John Hubbard and Laura Roth in the 1960s. We present the technique and apply it to the non-interacting electron and boson gas. We next consider the (many-body) Hubbard model and show how it yields the Stoner criterion for ferromagnetism. It is easily extendable to superconductivity and related problems. Our treatment is pedagogical and understandable to those with just an elementary understanding of second quantization.

cond-mat.stat-mech

Impact of Josephson junction array modes on fluxonium readout

Dispersive readout of superconducting qubits is often limited by readout-drive-induced transitions between qubit levels. While there is a growing understanding of such effects in transmon qubits, the case of highly nonlinear fluxonium qubits is more complex. We theoretically analyze measurement-induced state transitions (MIST) during the dispersive readout of a fluxonium qubit. We focus on a new mechanism: a simultaneous transition/excitation involving the qubit and an internal mode of the Josephson junction array in the fluxonium circuit. Using an adiabatic Floquet approach, we show that these new kinds of MIST processes can be relevant when using realistic circuit parameters and relatively low readout drive powers. They also contribute to excess qubit dephasing even after a measurement is complete. In addition to outlining basic mechanisms, we also investigate the dependence of such transitions on the circuit parameters. We find that with a judicious choice of frequency allocations or coupling strengths, these parasitic processes can most likely be avoided.

cond-mat.mes-hall

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

Quantum computing with discrete variable (DV, qubit) hardware is approaching the large scales necessary for computations beyond the reach of classical computers. However, important use cases such as quantum simulations of physical models containing bosonic modes, and quantum error correction are challenging for DV-only systems. Separately, hardware containing native continuous-variable (CV, oscillator) systems has received attention as an alternative approach, yet the universal control of such systems is non-trivial. In this work, we show that hybrid CV-DV hardware offers a great advantage in meeting these challenges, offering a powerful computational paradigm that inherits the strengths of both DV and CV processors. We provide a pedagogical introduction to CV-DV systems and the multiple abstraction layers needed to produce a full software stack connecting applications to hardware. We present a variety of new hybrid CV-DV compilation techniques, algorithms, and applications, including the extension of quantum signal processing concepts to CV-DV systems and strategies to simulate systems of interacting spins, fermions, and bosons. To facilitate the development of hybrid CV-DV processor systems, we introduce formal Abstract Machine Models and Instruction Set Architectures -- essential abstractions that enable developers to formulate applications, compile algorithms, and explore the potential of current and future hardware for realizing fault-tolerant circuits, modules, and processors. Hybrid CV-DV quantum computations are beginning to be performed in superconducting, trapped ion, and neutral atom platforms, and large-scale experiments are set to be demonstrated in the near future. We present a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and providing an architectural backbone to guide future development.

quant-ph

Fault-tolerant Fusion-based Quantum Computing with the Four-legged Cat Code

The four-legged cat code is a quantum error-correcting code designed to address the predominant error in bosonic modes: single-photon loss. It was the first such code to surpass the break-even point, thereby demonstrating the practical utility of quantum error correction. In this work, we propose a planar fault-tolerant architecture for this code by concatenating it with the XZZX code via fusion-based error-correction. To the best of our knowledge, this is the first 2D nearest-neighbor architecture for fault-tolerant fusion-based error-correction. We demonstrate how all the required operations, namely resource state preparation and Bell measurements, can be carried out using standard circuit-QED techniques, such as intercavity beam-splitter coupling, cavity displacements, cavity-transmon dispersive coupling, and transmon drives. We show analytically and numerically that all dominant hardware errors in the bosonic modes and control ancillae are corrected, to first-order, at the hardware level. Consequently, the outer XZZX code only needs to address smaller residual errors, which are quadratically suppressed, effectively doubling the architecture's fault-distance. Moreover, the performance of our architecture is not limited by unwanted nonlinearities such as cavity self-Kerr, and it avoids demanding coupling techniques like $χ$-matching or high-order coupling. Overall, our architecture substantially reduces the hardware complexity needed to achieve fault tolerance with the four-legged cat code.

quant-ph

Quantum Computing in Discrete- and Continuous-Variable Architectures

This thesis develops a theoretical framework for hybrid continuous-variable (CV) and discrete-variable (DV) quantum systems, with emphasis on quantum control, state preparation, and error correction. A central contribution is non-abelian quantum signal processing (NA-QSP), a generalization of quantum signal processing to settings where control parameters are non-commuting operators. Within this framework, we introduce the Gaussian-Controlled-Rotation (GCR) protocol, which enables high-fidelity control of CV states using DV ancillae. This approach allows for deterministic preparation of squeezed, cat, and Gottesman-Kitaev-Preskill (GKP) states without numerical optimization. Two previously unpublished contributions are included: (i) Chapter 2.3 introduces the Gaussian hierarchy, a classification of CV operations analogous to the Clifford hierarchy, offering a new lens for understanding CV gate sets; (ii) Chapter 5 presents an analytical framework for correcting photon loss in finite-energy GKP codes, introducing the notion of probabilistic error correction, providing insight into recent GKP experiments surpassing break-even thresholds. Overall, this work lays the groundwork for scalable, fault-tolerant quantum computation in hybrid CV-DV architectures, with applications to logical gate synthesis, readout, and hybrid algorithm design using ancilla oscillators.

quant-ph

Advances in Bosonic Quantum Error Correction with Gottesman-Kitaev-Preskill Codes: Theory, Engineering and Applications

Encoding quantum information into a set of harmonic oscillators is considered a hardware efficient approach to mitigate noise for reliable quantum information processing. Various codes have been proposed to encode a qubit into an oscillator -- including cat codes, binomial codes and Gottesman-Kitaev-Preskill (GKP) codes -- and are among the first to reach a break-even point for quantum error correction. Though GKP codes are widely recognized for their promise in quantum computation, they also facilitate near-optimal quantum communication rates in bosonic channels and offer the ability to safeguard arbitrary quantum states of oscillators. This review focuses on the basic working mechanism, performance characterization, and the many applications of GKP codes -- emphasizing recent experimental progress in superconducting circuit architectures and theoretical advancements in multimode GKP qubit codes and oscillators-to-oscillators (O2O) codes. We begin with a preliminary continuous-variable formalism needed for bosonic codes. We then proceed to the quantum engineering involved to physically realize GKP states. We take a deep dive into GKP stabilization and preparation in superconducting architectures and examine proposals for realizing GKP states in the optical domain (along with a concise review of GKP realization in trapped-ion platforms). Finally, we present multimode GKP qubits and GKP-O2O codes, examine code performance and discuss applications of GKP codes in quantum information processing tasks such as computing, communication, and sensing.

quant-ph

Quantum Error Correction of Qudits Beyond Break-even

Hilbert space dimension is a key resource for quantum information processing. A large Hilbert space is not only an essential requirement for quantum error correction, but it can also be advantageous for realizing gates and algorithms more efficiently. There has thus been considerable experimental effort in recent years to develop quantum computing platforms using qudits (d-dimensional quantum systems with d>2) as the fundamental unit of quantum information. Just as with qubits, quantum error correction of these qudits will be necessary in the long run, but to date error correction of logical qudits has not been demonstrated experimentally. Here we report the experimental realization of an error-corrected logical qutrit (d=3) and ququart (d=4) by employing the Gottesman-Kitaev-Preskill (GKP) bosonic code. Using a reinforcement learning agent, we optimize the GKP qutrit (ququart) as a ternary (quaternary) quantum memory and achieve beyond break-even error correction with a gain of 1.82 +/- 0.03 (1.87 +/- 0.03). This work represents a new way of leveraging the large Hilbert space of a harmonic oscillator for hardware-efficient quantum error correction.

quant-ph

Prithvi WxC: Foundation Model for Weather and Climate

Triggered by the realization that AI emulators can rival the performance of traditional numerical weather prediction models running on HPC systems, there is now an increasing number of large AI models that address use cases such as forecasting, downscaling, or nowcasting. While the parallel developments in the AI literature focus on foundation models -- models that can be effectively tuned to address multiple, different use cases -- the developments on the weather and climate side largely focus on single-use cases with particular emphasis on mid-range forecasting. We close this gap by introducing Prithvi WxC, a 2.3 billion parameter foundation model developed using 160 variables from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Prithvi WxC employs an encoder-decoder-based architecture, incorporating concepts from various recent transformer models to effectively capture both regional and global dependencies in the input data. The model has been designed to accommodate large token counts to model weather phenomena in different topologies at fine resolutions. Furthermore, it is trained with a mixed objective that combines the paradigms of masked reconstruction with forecasting. We test the model on a set of challenging downstream tasks namely: Autoregressive rollout forecasting, Downscaling, Gravity wave flux parameterization, and Extreme events estimation. The pretrained model with 2.3 billion parameters, along with the associated fine-tuning workflows, has been publicly released as an open-source contribution via Hugging Face.

cs.LG

Surface Code with Imperfect Erasure Checks

Recently, a lot of effort has been devoted towards designing erasure qubits in which dominant physical noise excites leakage states whose population can be detected and returned to the qubit subspace. Interest in these erasure qubits has been driven by studies showing that the requirements for fault-tolerant quantum error correction are significantly relaxed when noise in every gate operation is dominated by erasures. However, these studies assume perfectly accurate erasure checks after every gate operation which generally come with undesirable time and hardware overhead costs. In this work, we investigate the consequences of using an imperfect but overhead-efficient erasure check for fault-tolerant quantum error correction with the surface code. We show that, under physically reasonable assumptions on the imperfect erasure checks, the threshold error rate is still at least over twice that for Pauli noise. We also study the impact of imperfect erasure checks on the effective error distance and find that it degrades the effective distance under a general error model in which a qubit suffers from depolarizing noise when interacting with a leaked qubit. We then identify a more restrictive but realistic noise model for a qubit that interacts with a leaked qubit, under which the effective error distance is twice that for Pauli noise. We apply our analysis to recently proposed superconducting dual-rail erasure qubits and show that achieving good performance surface code quantum memories with relaxed system requirements is possible.

quant-ph

Fine-tuning of Geospatial Foundation Models for Aboveground Biomass Estimation

Global vegetation structure mapping is critical for understanding the global carbon cycle and maximizing the efficacy of nature-based carbon sequestration initiatives. Moreover, vegetation structure mapping can help reduce the impacts of climate change by, for example, guiding actions to improve water security, increase biodiversity and reduce flood risk. Global satellite measurements provide an important set of observations for monitoring and managing deforestation and degradation of existing forests, natural forest regeneration, reforestation, biodiversity restoration, and the implementation of sustainable agricultural practices. In this paper, we explore the effectiveness of fine-tuning of a geospatial foundation model to estimate above-ground biomass (AGB) using space-borne data collected across different eco-regions in Brazil. The fine-tuned model architecture consisted of a Swin-B transformer as the encoder (i.e., backbone) and a single convolutional layer for the decoder head. All results were compared to a U-Net which was trained as the baseline model Experimental results of this sparse-label prediction task demonstrate that the fine-tuned geospatial foundation model with a frozen encoder has comparable performance to a U-Net trained from scratch. This is despite the fine-tuned model having 13 times less parameters requiring optimization, which saves both time and compute resources. Further, we explore the transfer-learning capabilities of the geospatial foundation models by fine-tuning on satellite imagery with sparse labels from different eco-regions in Brazil.

cs.AI

Towards a Unified Quantum Protocol Framework: Classification, Implementation, and Use Cases

We present a framework for the unification and standardization of quantum network protocols, making their realization easier and expanding their use cases to a broader range of communities interested in quantum technologies. Our framework is available as an open-source repository, the Quantum Protocol Zoo. We follow a modular approach by identifying two key components: Functionality, which connects real-world applications; and Protocol, which is a set of instructions between two or many parties, at least one of which has a quantum device. Based on the different stages of the quantum internet and use-case in the commercialization of quantum communication, our framework classifies quantum cryptographic functionalities and the various protocol designs implementing these functionalities. Towards this classification, we introduce a novel concept of resource visualization for quantum protocols, which includes two interfaces: one to identify the building blocks for implementing a given protocol and another to identify accessible protocols when certain physical resources or functionalities are available. Such classification provides a hierarchy of quantum protocols based on their use-case and resource allocation. We have identified various valuable tools to improve its representation with a range of techniques, from abstract cryptography to graphical visualizations of the resource hierarchy in quantum networks. We elucidate the structure of the zoo and its primary features in this article to a broader class of quantum information scientists, physicists, computer science theorists and end-users. Since its introduction in 2018, the quantum protocol zoo has been a cornerstone in serving the quantum networks community in its ability to establish the use cases of emerging quantum internet networks. In that spirit we also provide some of the applications of our framework from different perspectives.

quant-ph

AI Foundation Models for Weather and Climate: Applications, Design, and Implementation

Machine learning and deep learning methods have been widely explored in understanding the chaotic behavior of the atmosphere and furthering weather forecasting. There has been increasing interest from technology companies, government institutions, and meteorological agencies in building digital twins of the Earth. Recent approaches using transformers, physics-informed machine learning, and graph neural networks have demonstrated state-of-the-art performance on relatively narrow spatiotemporal scales and specific tasks. With the recent success of generative artificial intelligence (AI) using pre-trained transformers for language modeling and vision with prompt engineering and fine-tuning, we are now moving towards generalizable AI. In particular, we are witnessing the rise of AI foundation models that can perform competitively on multiple domain-specific downstream tasks. Despite this progress, we are still in the nascent stages of a generalizable AI model for global Earth system models, regional climate models, and mesoscale weather models. Here, we review current state-of-the-art AI approaches, primarily from transformer and operator learning literature in the context of meteorology. We provide our perspective on criteria for success towards a family of foundation models for nowcasting and forecasting weather and climate predictions. We also discuss how such models can perform competitively on downstream tasks such as downscaling (super-resolution), identifying conditions conducive to the occurrence of wildfires, and predicting consequential meteorological phenomena across various spatiotemporal scales such as hurricanes and atmospheric rivers. In particular, we examine current AI methodologies and contend they have matured enough to design and implement a weather foundation model.

cs.LG

Encoding qubits in multimode grid states

Encoding logical quantum information in harmonic oscillator modes is a promising and hardware-efficient approach to the realization of a quantum computer. In this work, we propose to encode logical qubits in grid states of an ensemble of harmonic oscillator modes. We first discuss general results about these multimode bosonic codes; how to design them, how to practically implement them in different experimental platforms and how lattice symmetries can be leveraged to perform logical non-Clifford operations. We then introduce in detail two two-mode grid codes based on the hypercubic and D4 lattices, respectively, showing how to perform a universal set of logical operations. We demonstrate numerically that multimode grid codes have, compared to their single-mode counterpart, increased robustness against propagation of errors from ancillas used for error correction. Finally, we highlight some interesting links between multidimensional lattices and single-mode grid codes concatenated with qubit codes.

quant-ph