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The Heisenberg Representation of Quantum Computers

Canonical reference. 85% of citing Pith papers cite this work as background.

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Since Shor's discovery of an algorithm to factor numbers on a quantum computer in polynomial time, quantum computation has become a subject of immense interest. Unfortunately, one of the key features of quantum computers - the difficulty of describing them on classical computers - also makes it difficult to describe and understand precisely what can be done with them. A formalism describing the evolution of operators rather than states has proven extremely fruitful in understanding an important class of quantum operations. States used in error correction and certain communication protocols can be described by their stabilizer, a group of tensor products of Pauli matrices. Even this simple group structure is sufficient to allow a rich range of quantum effects, although it falls short of the full power of quantum computation.

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  • abstract Since Shor's discovery of an algorithm to factor numbers on a quantum computer in polynomial time, quantum computation has become a subject of immense interest. Unfortunately, one of the key features of quantum computers - the difficulty of describing them on classical computers - also makes it difficult to describe and understand precisely what can be done with them. A formalism describing the evolution of operators rather than states has proven extremely fruitful in understanding an important class of quantum operations. States used in error correction and certain communication protocols can
  • method Section 5 concludes with a summary of results and future directions. 2 Frame-Factored State Representation Standard state vector simulation scales exponentially with the total number of qubits in the system. However, fault-tolerant quantum circuits are typically dominated by Clifford operations, which can be tracked efficiently via the Gottesman-Knill theorem [37]. We utilize this structure by shifting from the standard Schrödinger picture to a hybrid representation that decouples the state into
  • background [40] Z. Wang,Topological Quantum Computation, American Mathematical Society (2010). [41] M.A. Nielsen and I.L. Chuang,Quantum Computation and Quantum Information, Cambridge University Press, 10th anniversary edition ed. (2010). [42] S. Aaronson and D. Gottesman,Improved simulation of stabilizer circuits,Phys. Rev. A70(2004) 052328 [quant-ph/0406196v5]. [43] D. Gottesman,The heisenberg representation of quantum computers, in22nd International Colloquium on Group Theoretical Methods in Physics, pp
  • background as starting points to include correlations, while the modern tools of tensor networks offer controlled, low-entanglement expansions around tensor-product states. Another notable class of states in the Hilbert space, that was only recently introduced in the many body-physics area [30], is that of stabilizer states. As first pointed out by Gottesmann and Knill [31], these states are special in that they can be prepared efficiently with classical computing [31,32], while being able to support high
  • background The study of the complexity of classical algorithms informs us that some problems cannot be solved by computers in reasonable timeframes. Quantum computers can solve these problems quickly, and the construction of these devices will bring profound technological changes in the upcoming decades. Some practical applications for which quantum algorithms currently exist include molecular simulation for drug discovery and material design [BGM+19, LBG+21, SBW+21, RBK+23], algorithms that break public-k
  • background advantage using photons, Science370, 1460 (2020), https://www.science.org/doi/pdf/10.1126/science.abe8770. [4] D. Gottesman, The heisenberg representation of quantum computers, arXiv preprint quant-ph/9807006 (1998). [5] S. Bravyi and A. Kitaev, Universal quantum computa- tion with ideal clifford gates and noisy ancillas, Physical Review A71, 022316 (2005). [6] A. Mari and J. Eisert, Positive wigner functions ren- der classical simulation of quantum computation ef- ficient, Physical Review Lette
  • background this by applying probabilistic inequalities such as Cheby- shev's inequality, Pr ∣ψ⟩∼ELU(ψ0) [∣sE(ψ)−∥E∥2 F∣≥kσ] ≤ 1 k2 , whereσ= √ Var(sE(ψ))denotes the standard de- viation. Error Kurtosis and Quantum Magic-In magic- state resource theory, Clifford operations and stabilizer states are considered "free" as a direct consequence of the Gottesman-Knill theorem [13, 14], which establishes their efficient classical simulability. In contrast, non- Clifford gates-though essential for achieving univers

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Sdim: A Qudit Stabilizer Simulator

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Sdim is the first open-source qudit stabilizer simulator supporting all dimensions, enabling circuit evaluation and sampling for qudit fault-tolerant quantum computing research.

Linear-Time T-Gate Optimization via Random Abstraction

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A randomized linear-time phase-folding algorithm using constant-width bitstring abstraction optimizes T-count in quantum circuits orders of magnitude faster than prior tools while achieving comparable reductions.

Nonstabilizerness Mpemba Effects

quant-ph · 2026-05-05 · unverdicted · novelty 7.0

In U(1)-symmetric random circuits, initial states with lower stabilizer Rényi entropy generate nonstabilizerness faster than those with higher entropy, with the effect also depending on spatial charge structure and extending to SU(2) circuits and Hamiltonian dynamics.

Magic-Informed Quantum Architecture Search

quant-ph · 2026-05-05 · unverdicted · novelty 7.0

A Monte Carlo Tree Search with GNN-based magic estimation biases quantum circuit search toward target nonstabilizerness levels and yields better results on ground-state energy and state approximation problems.

Clifft: Fast Exact Simulation of Near-Clifford Quantum Circuits

quant-ph · 2026-04-29 · unverdicted · novelty 7.0 · 2 refs

Clifft introduces a factored-state simulator that shifts exponential cost to a dynamic active subspace, generalizing Stim's compile-once model to near-Clifford circuits and enabling the first exact end-to-end simulations of magic-state cultivation over hundreds of billions of shots.

Nonlocal nonstabilizerness in free fermion models

quant-ph · 2026-04-29 · unverdicted · novelty 7.0

Nonlocal magic in fermionic Gaussian states is bounded by the entanglement spectrum of the covariance matrix, is extensive in the Haar ensemble, peaks at criticality in the Kitaev chain, and grows diffusively under random circuits.

The Structure of Circle Graph States

quant-ph · 2026-03-09 · unverdicted · novelty 7.0

Circle graphs are closed under r-local complementation and bipartite circle graph states correspond one-to-one with planar code states whose MBQC is classically simulable.

Stabilizer R\'enyi entropy of 3-uniform hypergraph states

quant-ph · 2026-02-27 · unverdicted · novelty 7.0

Stabilizer Rényi entropy of 3-uniform hypergraph states equals a matrix-rank expression, cutting computation from exponential in 3N to polynomial in N times exponential in N.

Operational interpretation of the Stabilizer Entropy

quant-ph · 2025-07-30 · unverdicted · novelty 7.0

The stabilizer Rényi entropy governs the exponential rate at which Clifford orbits become indistinguishable from Haar-random states and sets the optimal distinguishability from stabilizer states in property testing.

Rise and fall of nonstabilizerness via random measurements

quant-ph · 2025-07-15 · conditional · novelty 7.0

Analytical and numerical study of stabilizer nullity and Rényi entropies in monitored Clifford circuits shows quantized decay for computational measurements and size-dependent relaxation to a non-trivial steady state for rotated bases.

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