Dear all,
Very interesting seminar today @11 AM
---------- Forwarded message ----------
From: Peter Shor <shor(a)math.mit.edu>
Date: Thu, 24 Feb 2011 02:31:28 -0500
Subject: [QIP-Sem] QIP seminar, Thu 2/24, 11:00, 6-310, Sanders,Barry
To: qip-sem(a)mit.edu
MIT Quantum Information Processing seminar
Thursday 2/24 at 11:00 in 6-310
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Sanders,Barry (University of Calgary)
Simulating Time-Dependent Quantum Dynamics On A Quantum Computer
Abstract:
Since 1982, when Feynman first proposed efficiently simulating
Hamiltonian dynamics on a quantum computer as a way around classical-
computer intractability, great advances have been achieved in
developing general-purpose quantum-simulation algorithms for bounded-
error solutions that fully account for all consumed computational
resources. The primary focus has been on time-independent Hamiltonian
evolution, but time-dependent Hamiltonian evolution is also important
as it is central to quantum control and adiabatic processes. I report
our efficient quantum algorithm for simulating time-dependent
Hamiltonian evolution of general input states on a quantum computer
provided that the Hamiltonian is sufficiently smooth. The time cost of
our algorithm is close to linear in the evolution time, hence
comparable to algorithms for simulating time-independent Hamiltonian
evolution. Our algorithm is based on queries to an oracle holding the
Hamiltonian, and we assign unit cos
t per bit or qubit for oracle calls in contrast to previous work
wherein an oracle query yields an arbitrary number of bits or qubits
at constant cost. Our per-bit or per-qubit costing of oracle calls
reveals hitherto unnoticed simulation costs even for the case of
simulating time-independent Hamiltonian evolution. We also account
for discretization errors in the time and the representation of the
Hamiltonian. Consequently our algorithm not only enables simulation
of time-dependent quantum dynamics on a quantum computer but also
reduces to the time- independent evolution case and with a fair
assessment of oracle-query cost.
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