Publications (68)
Adaptive and Robust Watermark for Generative Tabular Data
Dung Daniel Ngo, Archan Ray, Akshay Seshadri +6
In recent years, watermarking generative tabular data has become a prominent framework to protect against the misuse of synthetic data. However, while most prior work in watermarki…
Optimal quantum-programmable projective measurements with coherent states
Niraj Kumar, Ulysse Chabaud, Elham Kashefi +2
We consider a device which can be programmed using coherent states of light to approximate a given projective measurement on an input coherent state. We provide and discuss three p…
Efficient quantum communications with multiplexed coherent state fingerprints
Niraj Kumar, Eleni Diamanti, Iordanis Kerenidis
We provide the first example of a communication model and a distributed task, for which there exists a realistic quantum protocol which is asymptotically more efficient than any cl…
A simple analysis of a quantum-inspired algorithm for solving low-rank linear systems
Tyler Chen, Junhyung Lyle Kim, Archan Ray +3
We describe and analyze a simple algorithm for sampling from the solution to a linear system . We assume…
Velocity of front propagation in the epidemic model
Niraj Kumar, Goutam Tripathy
We study front propagation in the irreversible epidemic model in one dimension. Here, we allow the particles and to diffuse with rates and , which, i…
Nonlinearity in Bacterial Population Dynamics: Proposal for Experiments for the Observation of Abrupt Transitions in Patches
V. M. Kenkre, Niraj Kumar
An explicit proposal for experiments leading to abrupt transitions in spatially extended bacterial populations in a Petri dish is presented on the basis of an exact formula obtaine…
Efficiency of isothermal molecular machines at maximum power
Christian Van den Broeck, Niraj Kumar, Katja Lindenberg
We derive upper and lower bounds for the efficiency of an isothermal molecular machine operating at maximum power. The upper bound is reached when the activated state is close to t…
Realization of a Quantum Streaming Algorithm on Long-lived Trapped-ion Qubits
Pradeep Niroula, Shouvanik Chakrabarti, Steven Kordonowy +30
Large classical datasets are often processed in the streaming model, with data arriving one item at a time. In this model, quantum algorithms have been shown to offer an unconditio…
Facile synthesis of 2D graphene oxide sheet enveloping ultrafine 1D LiMn2O4 as interconnected framework to enhance cathodic property for Li-ion battery
Niraj Kumar, Jassiel R. Rodriguez, Vilas G. Pol +1
Cubic spinel lithium manganese oxide (LiMn2O4) has been able to attract a great deal of attention over the years as a promising cathode material for large scale lithium ion batteri…
Exact distributions for stochastic gene expression models with bursting and feedback
Niraj Kumar, Thierry Platini, Rahul V. Kulkarni
Stochasticity in gene expression can give rise to fluctuations in protein levels and lead to phenotypic variation across a population of genetically identical cells. Recent experim…
MetaTT: A Global Tensor-Train Adapter for Parameter-Efficient Fine-Tuning
Javier Lopez-Piqueres, Pranav Deshpande, Archan Ray +3
We present MetaTT, a Tensor Train (TT) adapter framework for fine-tuning of pre-trained transformers. MetaTT enables flexible and parameter-efficient model adaptation by using a si…
Thermodynamics of a stochastic twin elevator
Niraj Kumar, Christian Van den Broeck, Massimiliano Esposito +1
We study the non-equilibrium thermodynamics of a single particle with two available energy levels, in contact with a classical (Maxwell-Boltzmann) or quantum (Bose-Einstein) heat b…
Nonlocality and conflicting interest games
Anna Pappa, Niraj Kumar, Thomas Lawson +4
Nonlocality enables two parties to win specific games with probabilities strictly higher than allowed by any classical theory. Nevertheless, all known such examples consider games…
On the Connection Between Quantum Pseudorandomness and Quantum Hardware Assumptions
Mina Doosti, Niraj Kumar, Elham Kashefi +1
This paper, for the first time, addresses the questions related to the connections between the quantum pseudorandomness and quantum hardware assumptions, specifically quantum physi…
Client-Server Identification Protocols with Quantum PUF
Mina Doosti, Niraj Kumar, Mahshid Delavar +1
Recently, major progress has been made towards the realisation of quantum internet to enable a broad range of classically intractable applications. These applications such as deleg…
Enhanced pseudocapacitance from finely ordered pristine alpha-MnO2 nanorods at favourably high current density using redox additive
Niraj Kumar, K. Guru Prasad, Arijit Sen +1
A flexible technique is developed using hydrochloric acid to modify the redox reaction between potassium permanganate and sodium nitrite in order to grow ultrafine alpha-MnO2 nanor…
Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem
Ruslan Shaydulin, Changhao Li, Shouvanik Chakrabarti +26
The quantum approximate optimization algorithm (QAOA) is a leading candidate algorithm for solving optimization problems on quantum computers. However, the potential of QAOA to tac…
Provably faster randomized and quantum algorithms for -means clustering via uniform sampling
Tyler Chen, Archan Ray, Akshay Seshadri +6
The -means algorithm (Lloyd's algorithm) is a widely used method for clustering unlabeled data. A key bottleneck of the -means algorithm is that each iteration requires time…
Certified randomness using a trapped-ion quantum processor
Minzhao Liu, Ruslan Shaydulin, Pradeep Niroula +29
While quantum computers have the potential to perform a wide range of practically important tasks beyond the capabilities of classical computers, realizing this potential remains a…
The Adjoint Is All You Need: Characterizing Barren Plateaus in Quantum Ansätze
Enrico Fontana, Dylan Herman, Shouvanik Chakrabarti +5
Using tools from the representation theory of compact Lie groups, we formulate a theory of Barren Plateaus (BPs) for parameterized quantum circuits whose observables lie in their d…
Anytime Training with Schedule-Free Spectral Optimization
Anuj Apte, Pranav Deshpande, Niraj Kumar +2
Standard neural network training relies on learning-rate schedules tied to a fixed horizon, leading to strong path dependence and costly re-tuning as data availability changes. Sch…
GPU-Parallelizable Randomized Sketch-and-Precondition for Linear Regression using Sparse Sign Sketches
Tyler Chen, Pradeep Niroula, Archan Ray +3
A litany of theoretical and numerical results have established the sketch-and-precondition paradigm as a powerful approach to solving large linear regression problems in standard c…
Moment Closure Approximations in a Genetic Negative Feedback Circuit
Mohammad Soltani, Cesar Vargas, Niraj Kumar +2
Auto-regulation, a process wherein a protein negatively regulates its own production, is a common motif in gene expression networks. Negative feedback in gene expression plays a cr…
Quantum Algorithm to Solve a Maze: Converting the Maze Problem into a Search Problem
Niraj Kumar, Debabrata Goswami
We propose a different methodology towards approaching a Maze problem. We convert the problem into a Quantum Search Problem (QSP), and its solutions are sought for using the iterat…
Morphological analysis of ultra fine α-MnO2 nanowires under different reaction conditions
Niraj Kumar, P. Dineshkumar, R. Rameshbabu +1
A simple hydrothermal method was developed for the synthesis of ultra fine single-crystal α-MnO2 nanowires by only using potassium permanganate and sodium nitrite in acidic soluti…
Quantum versus Classical Generative Modelling in Finance
Brian Coyle, Maxwell Henderson, Justin Chan Jin Le +3
Finding a concrete use case for quantum computers in the near term is still an open question, with machine learning typically touted as one of the first fields which will be impact…
Blind quantum machine learning with quantum bipartite correlator
Changhao Li, Boning Li, Omar Amer +11
Distributed quantum computing is a promising computational paradigm for performing computations that are beyond the reach of individual quantum devices. Privacy in distributed quan…
Crushing the Evidence: A Dual-Penalty Evasion Framework for Fooling White-Box Explainable AI Auditors
Niraj Kumar, Harsh Kasyap
Post-hoc model explainers such as LIME, SHAP, and Integrated Gradients are widely deployed to audit models in high-stakes sensitive domains, including finance, healthcare, and soci…
A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values
Tyler Chen, Akshay Seshadri, Mattia J. Villani +7
Shapley values have emerged as a critical tool for explaining which features impact the decisions made by machine learning models. However, computing exact Shapley values is diffic…
OntoCat: Automatically categorizing knowledge in API Documentation
Niraj Kumar, Premkumar Devanbu
Most application development happens in the context of complex APIs; reference documentation for APIs has grown tremendously in variety, complexity, and volume, and can be difficul…
Stochastic modeling of phenotypic switching and chemoresistance in cancer cell populations
Niraj Kumar, Gwendolyn M. Cramer, Seyed Alireza Zamani Dahaj +3
Phenotypic heterogeneity in cancer cells is widely observed and is often linked to drug resistance. In several cases, such heterogeneity in drug sensitivity of tumors is driven by…
Experimental demonstration of quantum advantage for NP verification with limited information
Federico Centrone, Niraj Kumar, Eleni Diamanti +1
In recent years, many computational tasks have been proposed as candidates for showing a quantum computational advantage, that is an advantage in the time needed to perform the tas…
QC-Forest: a Classical-Quantum Algorithm to Provably Speedup Retraining of Random Forest
Romina Yalovetzky, Niraj Kumar, Changhao Li +1
Random Forest (RF) is a popular tree-ensemble method for supervised learning, prized for its ease of use and flexibility. Online RF models require to account for new training data…
New Improvements in Solving Large LABS Instances Using Massively Parallelizable Memetic Tabu Search
Zhiwei Zhang, Jiayu Shen, Niraj Kumar +1
Low Autocorrelation Binary Sequences (LABS) is a particularly challenging binary optimization problem which quickly becomes intractable in finding the global optimum for problem si…
Entropy Distribution as a Fingerprint for Hallucinations in Generative Models
Mattia J. Villani, Pranav Deshpande, Akshay Seshadri +2
Large Language Models (LLMs) often generate factually incorrect outputs, commonly termed hallucinations, that undermine trust and limit deployment in high-stakes settings. Existing…
Prospects of Privacy Advantage in Quantum Machine Learning
Jamie Heredge, Niraj Kumar, Dylan Herman +5
Ensuring data privacy in machine learning models is critical, particularly in distributed settings where model gradients are typically shared among multiple parties to allow collab…
Des-q: a quantum algorithm to provably speedup retraining of decision trees
Niraj Kumar, Romina Yalovetzky, Changhao Li +2
Decision trees are widely adopted machine learning models due to their simplicity and explainability. However, as training data size grows, standard methods become increasingly slo…
Variational Quantum Cloning: Improving Practicality for Quantum Cryptanalysis
Brian Coyle, Mina Doosti, Elham Kashefi +1
Cryptanalysis on standard quantum cryptographic systems generally involves finding optimal adversarial attack strategies on the underlying protocols. The core principle of modellin…
Efficient Construction of Quantum Physical Unclonable Functions with Unitary t-designs
Niraj Kumar, Rawad Mezher, Elham Kashefi
Quantum physical unclonable functions, or QPUFs, are rapidly emerging as theoretical hardware solutions to provide secure cryptographic functionalities such as key-exchange, messag…
Precise control on morphology of ultrafine LiMn2O4 nanorods as supercapacitor electrode via two-step hydrothermal method
Niraj Kumar, K. Guru Prasad, T. Maiyalagan +1
We report three different synthesis routes while maintaining similar reaction conditions to choose an effective way to precisely control the growth of ultrafine one dimensional LiM…
Integral Transforms in a Physics-Informed (Quantum) Neural Network setting: Applications & Use-Cases
Niraj Kumar, Evan Philip, Vincent E. Elfving
In many computational problems in engineering and science, function or model differentiation is essential, but also integration is needed. An important class of computational probl…
Experimental demonstration of quantum advantage for one-way communication complexity
Niraj Kumar, Iordanis Kerenidis, Eleni Diamanti
The goal of demonstrating a quantum advantage with currently available experimental systems is of utmost importance in quantum information science. While this remains elusive for q…
A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts
Anant Khandelwal, Niraj Kumar
Wide usage of social media platforms has increased the risk of aggression, which results in mental stress and affects the lives of people negatively like psychological agony, fight…
CRUMB: Efficient Prior Fitted Network Inference via Distributionally Matched Context Batching
Jamie Heredge, Mattia J. Villani, Pranav Deshpande +2
Prior-fitted networks (PFNs) are a promising class of tabular foundation models that perform in-context learning, whereby the entire labelled training set is supplied as context, a…
Graph neural network initialisation of quantum approximate optimisation
Nishant Jain, Brian Coyle, Elham Kashefi +1
Approximate combinatorial optimisation has emerged as one of the most promising application areas for quantum computers, particularly those in the near term. In this work, we focus…
Extinction of Populations and the Schrödinger Equation: Analytic Calculations for Abrupt Transitions
Niraj Kumar, V. M. Kenkre
We study bifurcations in a spatially extended nonlinear system representing population dynamics with the help of analytic calculations based on the time-independent Schrödinger eq…
Quantum-Informed Portfolio Selection: An End-to-End Pipeline Validated on Trapped-Ion Hardware with Real Market Data
Romina Yalovetzky, Martin J. A. Schuetz, Zichang He +11
The paper presents a hybrid quantum‑classical pipeline (qReduMIS) that uses QAOA measurements to guide reductions for solving portfolio diversification formulated as a Maximum Inde…
Facile size-controllable synthesis of single crystalline \b{eta}-MnO2 nanorods under varying acidic strengths
Niraj Kumar, P. Dineshkumar, R. Rameshbabu +1
A simple one-pot hydrothermal synthesis of single crystalline beta-MnO2 nanorods with diameters in the range of 10-40nm is reported. During the synthesis process, the acid molariti…
Wold-type decomposition for doubly twisted left-invertible covariant representations
Niraj Kumar, Azad Rohilla, Harsh Trivedi
In this article, we have introduced the notion of a near-isometric covariant representation of a -correspondence. The other objective is to provide a unified approach to sever…
Privacy-preserving quantum federated learning via gradient hiding
Changhao Li, Niraj Kumar, Zhixin Song +2
Distributed quantum computing, particularly distributed quantum machine learning, has gained substantial prominence for its capacity to harness the collective power of distributed…
Optimal Fixed Priority Scheduling in Multi-Stage Multi-Resource Distributed Real-Time Systems
Niraj Kumar, Chuanchao Gao, Arvind Easwaran
This work studies fixed priority (FP) scheduling of real-time jobs with end-to-end deadlines in a distributed system. Specifically, given a multi-stage pipeline with multiple heter…
Front propagation in A2A, A3A process in 1d: velocity, diffusion and velocity correlations
Niraj Kumar, Goutam Tripathy
We study front propagation in the reaction diffusion process on a one dimensional (1d) lattice with hard core interaction between th…
Experimental demonstration of quantum advantage in communication complexity for Euclidean distance problem
Verena Yacoub, Niraj Kumar, Iordanis Kerenidis +1
When considering the complexity of communication protocols, the aim is to perform a certain task with the minimum amount of communication resources, such as time and transmitted in…
Transcriptional bursting in gene expression: analytical results for general stochastic models
Niraj Kumar, Abhyudai Singh, Rahul V. Kulkarni
Gene expression in individual cells is highly variable and sporadic, often resulting in the synthesis of mRNAs and proteins in bursts. Bursting in gene expression is known to impac…
Theory of possible effects of the Allee phenomenon on refugia of the Hantavirus epidemic
Niraj Kumar, M. N. Kuperman, V. M. Kenkre
We investigate possible effects of high order nonlinearities on the shapes of infection refugia of the Hantavirus epidemic. We replace Fisher-like equations that have been recently…
Expressive variational quantum circuits provide inherent privacy in federated learning
Niraj Kumar, Jamie Heredge, Changhao Li +3
Federated learning has emerged as a viable distributed solution to train machine learning models without the actual need to share data with the central aggregator. However, standar…
Practically feasible robust quantum money with classical verification
Niraj Kumar
We introduce a private quantum money scheme with the note verification procedure based on Sampling Matching, a problem in the one-way communication complexity model introduced by K…
Exploring the Role of Logically Related Non-Question Phrases for Answering Why-Questions
Niraj Kumar, Rashmi Gangadharaiah, Kannan Srinathan +1
In this paper, we show that certain phrases although not present in a given question/query, play a very important role in answering the question. Exploring the role of such phrases…
Stochastically driven single level quantum dot: a nano-scale finite-time thermodynamic machine and its various operational modes
Massimiliano Esposito, Niraj Kumar, Katja Lindenberg +1
We describe a single-level quantum dot in contact with two leads as a nanoscale finite-time thermodynamic machine. The dot is driven by an external stochastic force that switches i…
Applications of Certified Randomness
Omar Amer, Shouvanik Chakrabarti, Kaushik Chakraborty +8
Certified randomness can be generated with untrusted remote quantum computers using multiple known protocols, one of which has been recently realized experimentally. Unlike the ran…
Variational quantum algorithm for unconstrained black box binary optimization: Application to feature selection
Christa Zoufal, Ryan V. Mishmash, Nitin Sharma +6
We introduce a variational quantum algorithm to solve unconstrained black box binary optimization problems, i.e., problems in which the objective function is given as black box. Th…
A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks
Georgios Papadopoulos, Shaltiel Eloul, Yash Satsangi +4
The loss landscape of Variational Quantum Neural Networks (VQNNs) is characterized by local minima that grow exponentially with increasing qubits. Because of this, it is more chall…
Energy-Efficient Real-Time Job Mapping and Resource Management in Mobile-Edge Computing
Chuanchao Gao, Niraj Kumar, Arvind Easwaran
Mobile-edge computing (MEC) has emerged as a promising paradigm for enabling Internet of Things (IoT) devices to handle computation-intensive jobs. Due to the imperfect paralleliza…
Hardness of the Maximum Independent Set Problem on Unit-Disk Graphs and Prospects for Quantum Speedups
Ruben S. Andrist, Martin J. A. Schuetz, Pierre Minssen +9
Rydberg atom arrays are among the leading contenders for the demonstration of quantum speedups. Motivated by recent experiments with up to 289 qubits [Ebadi et al., Science 376, 12…
Two site self consistent method for front propagation in reaction-diffusion system
Niraj Kumar, Goutam Tripathy
We study front propagation in the reaction diffusion process on one dimensional lattice with hard core interaction between the particles. We propose a two site…
Quantum option pricing via the Karhunen-Loève expansion
Anupam Prakash, Yue Sun, Shouvanik Chakrabarti +8
We consider the problem of pricing discretely monitored Asian options over monitoring points where the underlying asset is modeled by a geometric Brownian motion. We provide tw…
Velocity and diffusion coefficient of reaction fronts in one dimension
Niraj Kumar, Goutam Tripathy
We study front propagation in the reversible reaction-diffusion system A + A <-> A on a 1-d lattice. Extending the idea of leading particle in studying the motion of the front we w…
Memory-induced anomalous dynamics: emergence of diffusion, subdiffusion, and superdiffusion from a single random walk model
Niraj Kumar, Upendra Harbola, Katja Lindenberg
We present a random walk model that exhibits asymptotic subdiffusive, diffusive, and superdiffusive behavior in different parameter regimes. This appears to be the first instance o…