About

Sandy Irani received her Ph.D. from UC Berkeley in 1991. Following her doctoral studies, she was a University of California President's Postdoctoral Fellow at UCSD. She joined the faculty of UC Irvine in 1992 and is currently a full professor and Associate Dean for Student Affairs at the Donald Bren School of Information & Computer Sciences. Her research has primarily focused on algorithm design and analysis, with an emphasis on applications to computing systems. In recent years, she has been working in the fields of Quantum Computation and Quantum Information Science.

Research topics

• Mathematics
• Physics
• Computer Science
• Artificial Intelligence
• Mathematical optimization
• Quantum mechanics
• Theoretical physics
• Applied mathematics
• Statistical physics
• Medical education
• Psychology
• Mathematics education
• Multimedia
• Mathematical analysis
• Algorithm

Selected publications

• Sublinear Work Parallel Quantum Algorithms for Computational Geometry

  Lecture notes in computer science · 2026-01-01

  book-chapterSenior author
  PublisherDOI

• Cycle Basis Algorithms for Reducing Maximum Edge Participation

  ArXiv.org · 2025-11-14

  preprintOpen accessSenior author

  We study the problem of constructing cycle bases of graphs with low maximum edge participation, defined as the maximum number of basis cycles that share any single edge. This quantity, though less studied than total weight or length, plays a critical role in quantum fault tolerance because it directly impacts the overhead of lattice surgery procedures used to implement an almost universal quantum gate set. Building on a recursive algorithm of Freedman and Hastings, we introduce a family of load-aware heuristics that adaptively select vertices and edges to minimize edge participation throughout the cycle basis construction. Our approach improves empirical performance on random regular graphs and on graphs derived from small quantum codes. We further analyze a simplified balls-into-bins process to establish lower bounds on edge participation. While the model differs from the cycle basis algorithm on real graphs, it captures what can be proven for our heuristics without using complex graph theoretic properties related to the distribution of cycles in the graph. Our analysis suggests that the maximum load of our heuristics grows on the order of (log n)^2. Our results indicate that careful cycle basis construction can yield significant practical benefits in the design of fault-tolerant quantum systems. This question also carries theoretical interest, as it is essentially identical to the basis number of a graph, defined as the minimum possible maximum edge participation over all cycle bases.

  PublisherOA PDFDOI

• Memory Hierarchy Design for Caching Middleware in the Age of NVM

  ArXiv.org · 2025-06-05 · 4 citations

  preprintOpen access

  Advances in storage technology have introduced Non-Volatile Memory, NVM, as a new storage medium. NVM, along with Dynamic Random Access Memory (DRAM), Solid State Disk (SSD), and Disk present a system designer with a wide array of options in designing caching middleware. Moreover, design decisions to replicate a data item in more than one level of a caching memory hierarchy may enhance the overall system performance with a faster recovery time in the event of a memory failure. Given a fixed budget, the key configuration questions are: Which storage media should constitute the memory hierarchy? What is the storage capacity of each hierarchy? Should data be replicated or partitioned across the different levels of the hierarchy? We model these cache configuration questions as an instance of the Multiple Choice Knapsack Problem (MCKP). This model is guided by the specification of each type of memory along with an application's database characteristics and its workload. Although MCKP is NP-complete, its linear programming relaxation is efficiently solvable and can be used to closely approximate the optimal solution. We use the resulting simple algorithm to evaluate design tradeoffs in the context of a memory hierarchy for a Key-Value Store (e.g., memcached) as well as a host-side cache (e.g., Flashcache). The results show selective replication is appropriate with certain failure rates and workload characteristics. With a slim failure rate and frequent data updates, tiering of data across the different storage media that constitute the cache is superior to replication.

  PublisherOA PDFDOI

• Local Dominance in Mixed-Strength Populations -- Fast Maximal Independent Set

  ArXiv.org · 2025-12-02

  preprintOpen accessSenior author

  In many natural and engineered systems, agents interact through local contests that determine which individuals become dominant within their neighborhoods. These interactions are shaped by inherent differences in strength, and they often lead to stable dominance patterns that emerge surprisingly quickly relative to the size of the population. This motivates the search for simple mathematical models that capture both heterogeneous agent strength and rapid convergence to stable local dominance. A widely studied abstraction of local dominance is the Maximal Independent Set (MIS) problem. In the Luby MIS protocol that provably converges quickly to an MIS, each agent repeatedly generates a strength value chosen uniformly and becomes locally dominant if its value is smaller than those of its neighbors. This provides a theoretical explanation for fast dominance convergence in populations of equal-strength agents and naturally raises the question of whether fast convergence also holds in the more realistic setting where agents are inherently mixed-strength. To investigate this question, we introduce the mixed-strength agents model, in which each agent draws its strength from its own distribution. We prove that the extension of the Luby MIS protocol where each agent repeatedly generates a strength value from its own distribution still exhibits fast dominance convergence, providing formal confirmation of the rapid convergence observed in many mixed-strength natural processes. We also show that heterogeneity can significantly change the dynamics of the process. In contrast to the equal-strength setting, a constant fraction of edges need not be eliminated per round. We construct a population and strength profile in which progress per round is asymptotically smaller, illustrating how inherent strength asymmetry produces qualitatively different global behavior.

  PublisherOA PDFDOI

• Commuting Local Hamiltonian Problem on 2D Beyond Qubits

  Communications in Mathematical Physics · 2025-10-03

  article1st author
  PublisherDOI

• Quantum Combine and Conquer and Its Applications to Sublinear Quantum Convex Hull and Maxima Set Construction

  ArXiv.org · 2025-04-08

  preprintOpen accessSenior author

  We introduce a quantum algorithm design paradigm called combine and conquer, which is a quantum version of the "marriage-before-conquest" technique of Kirkpatrick and Seidel. In a quantum combine-and-conquer algorithm, one performs the essential computation of the combine step of a quantum divide-and-conquer algorithm prior to the conquer step while avoiding recursion. This model is better suited for the quantum setting, due to its non-recursive nature. We show the utility of this approach by providing quantum algorithms for 2D maxima set and convex hull problems for sorted point sets running in $\tilde{O}(\sqrt{nh})$ time, w.h.p., where $h$ is the size of the output.

  PublisherOA PDFDOI

• Singing a MIS

  ArXiv.org · 2025-12-02

  preprintOpen access1st authorCorresponding

  We introduce a broadcast model called the singing model, where agents are oblivious of the size and structure of the communication network, even their immediate neighborhood. Agents can sing multiple notes which are heard by their neighbors. The model is a generalization of the beeping model, where agents can only emit sound at a single frequency. We give a simple and natural protocol where agents compete with their neighbors and their strength is reflected in the number of notes they sing. It converges in $O(log(n))$ time with high probability, where $n$ is the number of agents in the network. The protocol works in an asynchronous model where rounds vary in length and have different start times. It works with completely dynamic networks where agents can be faulty. The protocol is the first to converge to an MIS in logarithmic time for dynamic networks in a network oblivious model.

  PublisherOA PDFDOI

• Hamiltonian Complexity in the Thermodynamic Limit

  Journal of the ACM · 2025-10-06

  articleOpen accessSenior author

  Despite immense progress in quantum Hamiltonian complexity in the past decade, little is known about the computational complexity of quantum physics at the thermodynamic limit. In fact, even defining the problem properly is not straight forward. We study the complexity of estimating the ground energy of a fixed, translationally-invariant (TI) Hamiltonian in the thermodynamic limit, to within a given precision; this precision (given by n the number of bits of the approximation) is the sole input to the problem. Understanding the complexity of this problem captures how difficult it is for a physicist to measure or compute another digit in the approximation of a physical quantity in the thermodynamic limit. We show that this problem is contained in FEXP QMA-EXP and is hard for FEXP NEXP . This means that the problem is doubly exponentially hard in the size of the input. As an ingredient in our construction, we study the problem of computing the ground energy of translationally invariant finite 1D chains. A single Hamiltonian term, which is a fixed parameter of the problem, is applied to every pair of particles in a finite chain. In the finite case, the length of the chain is the sole input to the problem and the task is to compute an approximation of the ground energy. No thresholds are provided as in the standard formulation of the local Hamiltonian problem. We show that this problem is contained in FP QMA-EXP and is hard for FP NEXP . Our techniques employ a circular clock structure in which the ground energy is calibrated by the length of the cycle. This requires more precise expressions for the ground energies of the resulting matrices than were required for previous QMA-completeness constructions and even exact analytical bounds for the infinite case which we derive using techniques from spectral graph theory. To our knowledge, this is the first use of the circuit-to-Hamiltonian construction that shows hardness for a function class.

  PublisherDOI

• Quantum Metropolis Sampling via Weak Measurement

  arXiv (Cornell University) · 2024-06-23 · 2 citations

  preprintOpen accessSenior author

  Gibbs sampling is a crucial computational technique used in physics, statistics, and many other scientific fields. For classical Hamiltonians, the most commonly used Gibbs sampler is the Metropolis algorithm, known for having the Gibbs state as its unique fixed point. For quantum Hamiltonians, designing provably correct Gibbs samplers has been more challenging. [TOV+11] introduced a novel method that uses quantum phase estimation (QPE) and the Marriot-Watrous rewinding technique to mimic the classical Metropolis algorithm for quantum Hamiltonians. The analysis of their algorithm relies upon the use of a boosted and shift-invariant version of QPE which may not exist [CKBG23]. Recent efforts to design quantum Gibbs samplers take a very different approach and are based on simulating Davies generators [CKBG23,CKG23,RWW23,DLL24]. Currently, these are the only provably correct Gibbs samplers for quantum Hamiltonians. We revisit the inspiration for the Metropolis-style algorithm of [TOV+11] and incorporate weak measurement to design a conceptually simple and provably correct quantum Gibbs sampler, with the Gibbs state as its approximate unique fixed point. Our method uses a Boosted QPE which takes the median of multiple runs of QPE, but we do not require the shift-invariant property. In addition, we do not use the Marriott-Watrous rewinding technique which simplifies the algorithm significantly.

  PublisherOA PDFDOI

• Modified Iterative Quantum Amplitude Estimation is Asymptotically Optimal

  Society for Industrial and Applied Mathematics eBooks · 2023-01-01 · 6 citations

  book-chapter

  In this work, we provide the first QFT-free algorithm for Quantum Amplitude Estimation (QAE) that is asymptotically optimal while maintaining the leading numerical performance. QAE algorithms appear as a subroutine in many applications for quantum computers. The optimal query complexity achievable by a quantum algorithm for QAE is log queries, providing a speedup of a factor of 1/ε over any other classical algorithm for the same problem. The original algorithm for QAE utilizes the quantum Fourier transform (QFT) which is expected to be a challenge for near-term quantum hardware. To solve this problem, there has been interest in designing a QAE algorithm that avoids using QFT. Recently, the iterative QAE algorithm (IQAE) [1] was introduced with a near-optimal query complexity and small constant factors. In this work, we combine ideas from the preceding line of work to introduce a QFT-free QAE algorithm that maintains the asymptotically optimal query complexity while retaining small constant factors. We supplement our analysis with numerical experiments comparing our performance with IQAE where we find that our modifications retain the high performance, and in some cases even improve the numerical results.

  PublisherDOI

Recent grants

• AF: Small: Ground State Complexity in Quantum Many-Body Systems

  NSF · $499k · 2009–2014

Frequent coauthors

• Yuval Rabani

  125 shared

• Ronitt Rubinfeld

  Massachusetts Institute of Technology

  124 shared

• Martı́n Farach-Colton

  122 shared

• Michael Dinitz

  121 shared

• Avrim Blum

  121 shared

• Ravi Kumar

  121 shared

• Shubhangi Saraf

  Rutgers, The State University of New Jersey

  121 shared

• Robert Kleinberg

  121 shared

Awards & honors

• ACM Fellow (2023)
• Sandy Irani and Sameer Singh Receive Distinguished Faculty A…